The work flow of the experiment is as illustrated in Figure 14(a). The target is submerged in a water tank illustrated as Figure 14(b), muffled with foam material on the rear, lateral, and bottom sides to reduce the surplus reflection of sound waves. The sound wave form is gen‐ erated and detected by the ultrasound transducer and the results are sent to the ultrasound console (GE RT-3200) for detection and processing to form real time ultrasound images. These images are simultaneously shown on the screen of the RT-3200 and the display of the frame grabber. Once the micro-controller drives the subject to the designed angle, it triggers the frame grabber to capture and store a still image, which then moves on to the next de‐ signed angle; the process repeats until the micro-controller completes a 360 degree scanning. These still images are stored in sequence as the rotation index. The whole set of images is

**Figure 13.** Illustration of the relative positions between the collected image and the ultrasound transducer. The image shows the vertical axial direction with the image plane perpendicular to the surface of the ultrasound array. The spe‐ cific 7.5 MHz linear ultrasound array shown above has 128 elements. With two times of zoom-in setting, it covers two-

used to construct one final supercompounded ultrasonography.

controlled by a micro-controller.

pletes the supercompounding process.

gree of the images.

**3.2. Work flow**

thirds field of view.

In Figure 12(a) the PSF resultant picture shows an upside down triangle with long wings. Since the physical shape of the target is a point, the level of artifacts will be high. The axial reverberation is angular dependent artifacts, and the size of lateral resolution is limited by both the transducer and different focal zones. By reducing the stepping angle of spinning α from 0° (360°) to 60°, and then to 30°, the compounded PSF shrinks to a point (Figure 12(b), (c)). This suggests that the spin average can remove the angular dependent artifacts and dis‐ tortion caused by focusing.

**Figure 12.** The PSF of a metal pin head (a) the original PSF without spin average - α = 0° (b) the PSF with 6 images compounded - α = 60° (c) the PSF with 12 images compounded - α = 30°

#### **3. Materials and methods**

#### **3.1. Introduction**

The experiment setup focuses on utilizing a conventional ultrasound imaging system (GE RT-3200) to test the spin average theory and the supercompounding concept. The experi‐ mental apparatus – the three-dimensional moving platform – is designed in two parts, im‐ age acquisition and image processing.

Since a complete spin average is an integral between 0 and 2π, the images or data has to be acquired around the targets of interest. In order to do so, either a transducer has to be rotat‐ ed around the targets or the targets themselves have to be rotated around the center point. The latter option – objects rotating around a center point – is used in this experiment to ach‐ ieve better results in demonstrating the concept of the spin average theory and supercom‐ pounding technique. One reason to favor this option is that the rotation of the targets of interest allows us to accomplish the goal without moving or vibrating the transducer. An‐ other reason is that the transducer will always have solid contact with the surface of the tar‐ get container. As a result, our objects are mounted on a rod connected to a DC gear motor controlled by a micro-controller.

The same micro-controller also controls image acquisition. Once the target is rotated to the designed angle, the micro-controller triggers the frame grabber to capture the image and to store the results in a specific order. Such order is the index for quantifying the rotational de‐ gree of the images.

Since the conventional ultrasound images are usually shown in the vertical axial direction, the transducer is positioned at the top of the image shown as Figure 13. In order to have all images aligned in the same coordinate system, a coordinate transformation (derotation) has to be applied on each image at a specific angle based on the rotation index around the center of the rotation. After derotation, all images are ready for the recombination, which com‐ pletes the supercompounding process.

#### **3.2. Work flow**

**2.4. Regularized point spread function**

94 Medical Imaging in Clinical Practice

tortion caused by focusing.

**3. Materials and methods**

age acquisition and image processing.

**3.1. Introduction**

Spin average reduces artifacts, reveals the true shapes of physical components and regular‐ izes the point spread functions which means having a more symmetric, more uniform and tighter PSF which is less space invariant. For practical purposes, the quality of results is in‐ versely related to the size of the travel step α. The regularization of the PSF function is shown in Figure 12. In this illustration, a metal pin head is used to simulate a point target. In Figure 12(a) the PSF resultant picture shows an upside down triangle with long wings. Since the physical shape of the target is a point, the level of artifacts will be high. The axial reverberation is angular dependent artifacts, and the size of lateral resolution is limited by both the transducer and different focal zones. By reducing the stepping angle of spinning α from 0° (360°) to 60°, and then to 30°, the compounded PSF shrinks to a point (Figure 12(b), (c)). This suggests that the spin average can remove the angular dependent artifacts and dis‐

**Figure 12.** The PSF of a metal pin head (a) the original PSF without spin average - α = 0° (b) the PSF with 6 images

The experiment setup focuses on utilizing a conventional ultrasound imaging system (GE RT-3200) to test the spin average theory and the supercompounding concept. The experi‐ mental apparatus – the three-dimensional moving platform – is designed in two parts, im‐

Since a complete spin average is an integral between 0 and 2π, the images or data has to be acquired around the targets of interest. In order to do so, either a transducer has to be rotat‐ ed around the targets or the targets themselves have to be rotated around the center point. The latter option – objects rotating around a center point – is used in this experiment to ach‐ ieve better results in demonstrating the concept of the spin average theory and supercom‐ pounding technique. One reason to favor this option is that the rotation of the targets of interest allows us to accomplish the goal without moving or vibrating the transducer. An‐ other reason is that the transducer will always have solid contact with the surface of the tar‐

compounded - α = 60° (c) the PSF with 12 images compounded - α = 30°

The work flow of the experiment is as illustrated in Figure 14(a). The target is submerged in a water tank illustrated as Figure 14(b), muffled with foam material on the rear, lateral, and bottom sides to reduce the surplus reflection of sound waves. The sound wave form is gen‐ erated and detected by the ultrasound transducer and the results are sent to the ultrasound console (GE RT-3200) for detection and processing to form real time ultrasound images. These images are simultaneously shown on the screen of the RT-3200 and the display of the frame grabber. Once the micro-controller drives the subject to the designed angle, it triggers the frame grabber to capture and store a still image, which then moves on to the next de‐ signed angle; the process repeats until the micro-controller completes a 360 degree scanning. These still images are stored in sequence as the rotation index. The whole set of images is used to construct one final supercompounded ultrasonography.

**Figure 13.** Illustration of the relative positions between the collected image and the ultrasound transducer. The image shows the vertical axial direction with the image plane perpendicular to the surface of the ultrasound array. The spe‐ cific 7.5 MHz linear ultrasound array shown above has 128 elements. With two times of zoom-in setting, it covers twothirds field of view.

**Figure 15.** Illustration of the dynamic range of a gray scale image. Values between absolute black and white are divid‐

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The resulting images are stored as bitmap image files (bmp) in a 24-bit bitmaps format in‐ cluding three color layers (green, blue and red). Bitmap data (pixel array) describes the im‐ age pixel by pixel. 24-bit represents 24 bits per pixel. For instance, the recorded ultrasound image in the experiment is 640 pixels by 480 pixels. That leads to 307,200 pixels in total. Each pixel is 24 bits, which gives us 7,372,800 bits per image, 921,600 bytes (1 byte = 8 bits) or 900

Since the ultrasound images used in the experiment are black and white (gray scale) images, the data recorded in the three color layers are the same. To reduce image processing time, only one layer of data is used. The layers are segregated and only the green layer is kept. It

As is stated in the discussion in section 3.1, to process the spin average concept, involved images must be in the same coordinate system. Each individual image has to be derotated around the center of rotation (corresponding to the relative position between the ultrasound

**Figure 16.** Illustration of the relative position between the shaft of the gear motor and the ultrasound transducer. In the experiment, the object is mounted on the output shaft of the gear motor and is rotated at the center of rotation.

Figure 17 (a) and (b) illustrate how a triangular object is imaged. (a) is taken when the object is at the starting position. In order to perform spin average concept, the object has to be im‐ aged from other angles. (b) is collected when the object is rotated 30 degrees counter clock‐ wise around the center of the rotation. (c) and (d) are the results of (a) and (b) respectively. As the results shown in (c) and (d), the objects are shown in two different coordinate sys‐

ed into 255 levels. These levels are called "gray levels".

k (1 k = 1024 bytes) in other words.

*3.3.3. Image rotation*

leads to a smaller image size – 300k (one-third of 900k).

transducer and the output shaft of the gear motor shown as Figure 16).

**Figure 14.** The work flow and the illustration of the experiments setup. The target of interest is mounted on the out‐ put shaft of the DC gear motor. Micro-controller controls the rotation of the motor. Once it is rotated to the designed angle, the micro-controller sends capturing signal to the frame grabber to store the image that is concurrently being received from the GE RT-3200 ultrasound console.

#### **3.3. Processing of ultrasound images**

#### *3.3.1. Software*

The software used to process the raw image data for supercompounding is MATLAB (ma‐ trix laboratory). MATLAB is a numerical computing environment that allows matrix manip‐ ulations, plotting functions and data and implementation of algorithms to solve the mathematic issues. Behind the mathematic operations, it is also a tool to create a user inter‐ face, correlating with programs written in other languages, such as C++.

The reasons why MATLAB is used to process the resultant images are (1) the image itself is a matrix and (2) manipulating matrices is one of the major strengths of MATLAB. With many built-in tool boxes, most of the ordinary image operation can be accomplished easily.

#### *3.3.2. Images*

The image is pixelized data. Each pixel (point) in the image corresponds to an intensity val‐ ue ranging from 0 to 255, the dynamic range of the display. In an ultrasound imaging sys‐ tem, the image is black and white, or in the so-called "gray scale". "Zero" represents black and "255" represents white. Between black and white there are different shades of gray il‐ lustrated as Figure 15.

**Figure 15.** Illustration of the dynamic range of a gray scale image. Values between absolute black and white are divid‐ ed into 255 levels. These levels are called "gray levels".

The resulting images are stored as bitmap image files (bmp) in a 24-bit bitmaps format in‐ cluding three color layers (green, blue and red). Bitmap data (pixel array) describes the im‐ age pixel by pixel. 24-bit represents 24 bits per pixel. For instance, the recorded ultrasound image in the experiment is 640 pixels by 480 pixels. That leads to 307,200 pixels in total. Each pixel is 24 bits, which gives us 7,372,800 bits per image, 921,600 bytes (1 byte = 8 bits) or 900 k (1 k = 1024 bytes) in other words.

Since the ultrasound images used in the experiment are black and white (gray scale) images, the data recorded in the three color layers are the same. To reduce image processing time, only one layer of data is used. The layers are segregated and only the green layer is kept. It leads to a smaller image size – 300k (one-third of 900k).

#### *3.3.3. Image rotation*

(a) Work flow

96 Medical Imaging in Clinical Practice

received from the GE RT-3200 ultrasound console.

**3.3. Processing of ultrasound images**

*3.3.1. Software*

*3.3.2. Images*

lustrated as Figure 15.

(b) Illustration of the experiment setup

**Figure 14.** The work flow and the illustration of the experiments setup. The target of interest is mounted on the out‐ put shaft of the DC gear motor. Micro-controller controls the rotation of the motor. Once it is rotated to the designed angle, the micro-controller sends capturing signal to the frame grabber to store the image that is concurrently being

The software used to process the raw image data for supercompounding is MATLAB (ma‐ trix laboratory). MATLAB is a numerical computing environment that allows matrix manip‐ ulations, plotting functions and data and implementation of algorithms to solve the mathematic issues. Behind the mathematic operations, it is also a tool to create a user inter‐

The reasons why MATLAB is used to process the resultant images are (1) the image itself is a matrix and (2) manipulating matrices is one of the major strengths of MATLAB. With many built-in tool boxes, most of the ordinary image operation can be accomplished easily.

The image is pixelized data. Each pixel (point) in the image corresponds to an intensity val‐ ue ranging from 0 to 255, the dynamic range of the display. In an ultrasound imaging sys‐ tem, the image is black and white, or in the so-called "gray scale". "Zero" represents black and "255" represents white. Between black and white there are different shades of gray il‐

face, correlating with programs written in other languages, such as C++.

As is stated in the discussion in section 3.1, to process the spin average concept, involved images must be in the same coordinate system. Each individual image has to be derotated around the center of rotation (corresponding to the relative position between the ultrasound transducer and the output shaft of the gear motor shown as Figure 16).

**Figure 16.** Illustration of the relative position between the shaft of the gear motor and the ultrasound transducer. In the experiment, the object is mounted on the output shaft of the gear motor and is rotated at the center of rotation.

Figure 17 (a) and (b) illustrate how a triangular object is imaged. (a) is taken when the object is at the starting position. In order to perform spin average concept, the object has to be im‐ aged from other angles. (b) is collected when the object is rotated 30 degrees counter clock‐ wise around the center of the rotation. (c) and (d) are the results of (a) and (b) respectively. As the results shown in (c) and (d), the objects are shown in two different coordinate sys‐ tems. Therefore, a coordinate transformation has to be performed on the images to keep the objects in the same coordinate system. A 30-degree-clockwise rotation is performed on Fig‐ ure 17 (d) to transform the image to the same coordinate system as (e) which is 0 degree ro‐ tation from (c). Since the coordinate transformation is the second time of rotation and is in the opposite direction to neutralize the first time of rotation, we call it derotation.

{

Figure 18) can be derived geometrically.

The coordinates of P on dx-dz plane is (*OQ*

{*OQ* -

*PQ* -

Equation 11 can be solved and rewritten as equation 9.

*3.3.4. Supercompounding*

lowing equation,

=*OU* -

=*RS* -

The relation in general form is denoted as following equations.

{

*f* 2*s*(*r*)=*∫* 0

> *N* ∑ *M* =1 *N*

*f* 2*s*(*r*) = 1

+ *SU* -

*Dx* =*dx*cos *θ* + *dz*sin *θ Dz* =*dz*cos *θ* - *dx*sin *θ*

=*OS* -

=*PS* -

*dx* =*Dx*cos *θ* - *Dz*sin *θ dz* =*Dz*cos *θ* + *Dx*sin *θ*

As discussed in section 2.3 and 2.4, the supercompounding technique is based on the twodimensional spin average concept. To satisfy equation 7 in practice, the discrete method is used in the present study. By rotating the object and summing a multiplicity of images, we can approximate a continuous spin average. In theory, the rotational stepping degree θ is infinitely small. In practice, the angular stepping degree of the motor represents the travel step in the theory and equation 7 can be rewritten discretely as the following equation,

where f*2*s(r) is the two-dimensional spin average function, f*d* represents the image domains after the derotation process, θ is the stepping degree, M is 1,2,3,…,N and N is the total num‐ ber of the derotated images (N=2π/θ). Either equation 7 or 12 is described in the polar coor‐ dinate system. To process the concept on the images which is described as a pixel grid, Cartesian coordinate system can be used to further simplify the process illustrated in the fol‐

where dx and dz are distances of the pixel from the center of rotation, Dx and Dz the new coordinates after transposition. The relationship between initial and rotated axes (shown as

> , ) *QP* -

and is (*OS*

cos *θ* - *PS* sin *θ*

cos *θ* + *OS* -

sin *θ*

2*π f d* (*r*cos *θ*, *r*sin *θ*)*dθ* (12)

*f d* (*r*cos *Mθ*, *r*sin *Mθ*) (13)

) on Dx-Dz plane.

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(9)

99

(10)

(11)

**Figure 17.** Illustration of derotation. (a) and (b) illustrate how a triangular object is rotated and then imaged. (c) and (d) are the images after derotation. (e) is the compounded image of (e) and (f).

**Figure 18.** dx and dz are the initial axes and Dx and Dz are the rotated axes by θ. P is the demonstration point and O is the origin.

All images are electronically derotated around the center of rotation in MATLAB. Coordi‐ nates mapping the derotated images to the initial position can be obtained using the stand‐ ard formula for axes rotation [20]:

$$\begin{cases} Dx = dx \cos \theta + dz \sin \theta \\\\ Dz = dz \cos \theta \ -dz \sin \theta \end{cases} \tag{9}$$

where dx and dz are distances of the pixel from the center of rotation, Dx and Dz the new coordinates after transposition. The relationship between initial and rotated axes (shown as Figure 18) can be derived geometrically.

The coordinates of P on dx-dz plane is (*OQ* - , ) *QP* and is (*OS* - , *PS* - ) on Dx-Dz plane.

$$\begin{aligned} \stackrel{\cdot}{OQ = OU \cdot QU = \stackrel{\cdot}{OS \cos \theta} \stackrel{\cdot}{\cdot} \stackrel{\cdot}{PS \sin \theta}} \\ \stackrel{\cdot}{PQ = RS + SU = PS \cos \theta + OS \sin \theta} \end{aligned} \tag{10}$$

The relation in general form is denoted as following equations.

$$\begin{cases} d\mathbf{x} = D\mathbf{x}\cos\theta \ -D\mathbf{z}\sin\theta \\\\ d\mathbf{z} = D\mathbf{z}\cos\theta + D\mathbf{x}\sin\theta \end{cases} \tag{11}$$

Equation 11 can be solved and rewritten as equation 9.

#### *3.3.4. Supercompounding*

tems. Therefore, a coordinate transformation has to be performed on the images to keep the objects in the same coordinate system. A 30-degree-clockwise rotation is performed on Fig‐ ure 17 (d) to transform the image to the same coordinate system as (e) which is 0 degree ro‐ tation from (c). Since the coordinate transformation is the second time of rotation and is in

**Figure 17.** Illustration of derotation. (a) and (b) illustrate how a triangular object is rotated and then imaged. (c) and

**Figure 18.** dx and dz are the initial axes and Dx and Dz are the rotated axes by θ. P is the demonstration point and O is

All images are electronically derotated around the center of rotation in MATLAB. Coordi‐ nates mapping the derotated images to the initial position can be obtained using the stand‐

(d) are the images after derotation. (e) is the compounded image of (e) and (f).

the origin.

98 Medical Imaging in Clinical Practice

ard formula for axes rotation [20]:

the opposite direction to neutralize the first time of rotation, we call it derotation.

As discussed in section 2.3 and 2.4, the supercompounding technique is based on the twodimensional spin average concept. To satisfy equation 7 in practice, the discrete method is used in the present study. By rotating the object and summing a multiplicity of images, we can approximate a continuous spin average. In theory, the rotational stepping degree θ is infinitely small. In practice, the angular stepping degree of the motor represents the travel step in the theory and equation 7 can be rewritten discretely as the following equation,

$$f\_2 s(r) = \zeta\_0^{2\pi} f\_d \{ r \cos \theta\_r \, r \sin \theta \} d\theta \tag{12}$$

$$f\_2 s \begin{pmatrix} r \\ r \end{pmatrix} = \frac{1}{N} \sum\_{M=1}^{N} f\_d \{ r \cos M\theta, \ r \sin M\theta \} \tag{13}$$

where f*2*s(r) is the two-dimensional spin average function, f*d* represents the image domains after the derotation process, θ is the stepping degree, M is 1,2,3,…,N and N is the total num‐ ber of the derotated images (N=2π/θ). Either equation 7 or 12 is described in the polar coor‐ dinate system. To process the concept on the images which is described as a pixel grid, Cartesian coordinate system can be used to further simplify the process illustrated in the fol‐ lowing equation,

$$\int f\_2 \mathbf{s} \begin{pmatrix} D\mathbf{x} \ \prime \ D\mathbf{z} \end{pmatrix} = \frac{1}{N} \sum\_{M=1}^{N} f\_{d,M} \begin{Bmatrix} D\mathbf{x} \ \prime \ D\mathbf{z} \end{Bmatrix} \tag{14}$$

**•** Non-circular point spread function (PSF): As stated in section 2.4, the PSF is not a circular point in the conventional ultrasound imagers. This is because the lateral resolution is sev‐ eral times worse than the axial resolution. Therefore, after the image convolves with the PSF, the output image from the ultrasound system could be several times more blurred in the lateral direction than in axial. To evaluate the supercompounded PSF, the metal pin

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**•** Circular object: Circular objects generally do not appear circular on ultrasound images. The edges of the two-side walls are usually missing because the incident ultrasound waves are reflected away-from instead of back-to the transducer. The ultrasound system cannot receive any signals coming from those regions and causes the image to dropout at oblique angles. The dissected porcine aortic root is used to test the imaging performance of circular objects like blood vessels or cysts. The tests of the aortic roots are collaborated experiments with Dr. Wei Sun [21] (Biomedical Engineering, University of Connecticut).

**Figure 20.** Example of supercompounding process with a porcine aorta. The results of (a) to (j) are the part of the derotated images taken from the every 1.68 degrees. (k) is the supercompounded image superimposed from 214

The metal pin heads used in the study are 0.5 millimeter diameter pin heads. They were se‐ lected for their small size and for their material, which is highly reflective when placed in water due to the acoustic impedance mismatch. Sound waves that hits this material cause

derotated images. Note multiple nodes of enhanced echogenicity become clear after supercompounding.

head is selected.

**4.1. Imaging of metal pin heads**

where Dx and Dz are coordinates in Cartesian system after the derotation transformation and f*d,M* represents the numbers of derotated images. Once the raw images are derotated properly, they can be substituted into equation 13 easily. The process can be broken down into three phases, (1) derotate raw images, (2) superimpose derotated images and (3) aver‐ age the result. The illustration and the example of the supercompounding process are shown as Figures 19 and 20.

**Figure 19.** Illustration of the supercompounding process. The triangular object is rotated every 36 degrees counterclockwise and it makes the clockwise derotation. The supercompounded image is the superimposed image of all dero‐ tated images.

#### **4. Results**

In this research, two objects are studied: the metal pin heads and the dissected porcine aortic root. Each object is chosen for different purposes and together allows us to observe the per‐ formances of the spin average concept and the supercompounding technique under differ‐ ent circumstances. These selected objects also represent some issues that conventional ultrasound imagers face, which include the following:

**Figure 20.** Example of supercompounding process with a porcine aorta. The results of (a) to (j) are the part of the derotated images taken from the every 1.68 degrees. (k) is the supercompounded image superimposed from 214 derotated images. Note multiple nodes of enhanced echogenicity become clear after supercompounding.

#### **4.1. Imaging of metal pin heads**

*f* 2*s*(*Dx*, *Dz*) = 1

(a) Raw images

(b) Derotated images

ultrasound imagers face, which include the following:

(c) Supercompounded image

**Figure 19.** Illustration of the supercompounding process. The triangular object is rotated every 36 degrees counterclockwise and it makes the clockwise derotation. The supercompounded image is the superimposed image of all dero‐

In this research, two objects are studied: the metal pin heads and the dissected porcine aortic root. Each object is chosen for different purposes and together allows us to observe the per‐ formances of the spin average concept and the supercompounding technique under differ‐ ent circumstances. These selected objects also represent some issues that conventional

shown as Figures 19 and 20.

100 Medical Imaging in Clinical Practice

tated images.

**4. Results**

*N* ∑ *M* =1 *N*

where Dx and Dz are coordinates in Cartesian system after the derotation transformation and f*d,M* represents the numbers of derotated images. Once the raw images are derotated properly, they can be substituted into equation 13 easily. The process can be broken down into three phases, (1) derotate raw images, (2) superimpose derotated images and (3) aver‐ age the result. The illustration and the example of the supercompounding process are

*f d* ,*M* (*Dx*, *Dz*) (14)

The metal pin heads used in the study are 0.5 millimeter diameter pin heads. They were se‐ lected for their small size and for their material, which is highly reflective when placed in water due to the acoustic impedance mismatch. Sound waves that hits this material cause massive reverberation, i.e. multiple reflections, in which create parallel lines under the ob‐ ject on the ultrasound images. Therefore, in addition to observing the offset of improving the point spread function, this test can be used to observe how supercompounding handles reflective material layers. Figure 21 is one of the raw images of the metal pin heads. The metal pin heads are arranged as a capital letter 'L'. All images are taken with the 7.5MHz linear transducer.

Pins 1-6 are all either three or four pixels in axial size regardless on reverberation artifacts.

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The lateral sizes, however, vary depending upon the depths and the distance from the focal zone. The pin closer to the focal zone (27 mm) has better lateral resolution. The average size in the lateral direction is 3.59 ± 2.38 mm, which is seven times larger than the actual size. The best result is the pin number 3. It is 1.7 mm away from the focal zone (27mm – 25.32mm = 1.7mm), and with a lateral size is 1.83 mm, it is still three times larger than the actual size of the metal pin head. Figure 22 compares the raw image with the supercompounded image

**Figure 22.** Supercompounded image. Comparing to Figure 4.1, the artifacts are significantly reduced and the result

In Figure 22, six points appear instead of the T-shape. The artifacts from reverberation are

**Pin number Lateral size Axial Size Depth** 5 px 6 px N/A 5 px 5 px N/A 5 px 5 px N/A 4 px 6 px N/A 4 px 4 px N/A 4 px 4 px N/A

The average size in lateral direction is 0.86 ± 0.09 mm and 0.835 ± 0.15 mm in the axial. They are one and half times larger than the actual size of the pin head in all directions. As dis‐ cussed in section 2.5, the supercompounded PSF should be closer to the axial resolution.

shows each point has similar circular shape and is tighter and more symmetric.

**Table 2.**

significantly reduced as well. The measurements are included in Table 2.

This translates to an average size of 0.56 ± 0.086 mm.

constructed from 214 derotated raw images.

**Figure 21.** Metal pin heads are arranged as a letter L. The six objects are shown as "T" like shape instead of point like. The axial artifacts are caused by the reverberations inside the metal pin heads. The reverberations mislead the ultra‐ sound imager that there are the same objects in consecutive depths. It makes multiple lines behind the objects. The pin number 1 to 3 and group 4, 5 and 6 are aligned at different depths. The focal zone is 27 millimeter in depth. It is at the middle of the pin number 3 and group 4, 5 and 6; therefore, the pin number 1, 2 and 3 are superficial to the focal point and the group 4, 5 and 6 are deep to the focal point.

Figure 21 shows artifacts on the image of six objects caused by reverberation. The objects are the metal pin heads and they should appear point like instead of a T-shaped with long tails (reverberations) and wings (side lobes). As stated in section 2.4, the point spread function is space variant in most conventional ultrasound imagers and causes size differences for the same objects depending on how far the object is away from the focal zone. In Figure 21, each pin represents the point spread function at one spatial position. The measurements of di‐ mensions are described in Table 1.

Pins 1-6 are all either three or four pixels in axial size regardless on reverberation artifacts. This translates to an average size of 0.56 ± 0.086 mm.

The lateral sizes, however, vary depending upon the depths and the distance from the focal zone. The pin closer to the focal zone (27 mm) has better lateral resolution. The average size in the lateral direction is 3.59 ± 2.38 mm, which is seven times larger than the actual size. The best result is the pin number 3. It is 1.7 mm away from the focal zone (27mm – 25.32mm = 1.7mm), and with a lateral size is 1.83 mm, it is still three times larger than the actual size of the metal pin head. Figure 22 compares the raw image with the supercompounded image constructed from 214 derotated raw images.

**Figure 22.** Supercompounded image. Comparing to Figure 4.1, the artifacts are significantly reduced and the result shows each point has similar circular shape and is tighter and more symmetric.

In Figure 22, six points appear instead of the T-shape. The artifacts from reverberation are significantly reduced as well. The measurements are included in Table 2.

#### **Table 2.**

massive reverberation, i.e. multiple reflections, in which create parallel lines under the ob‐ ject on the ultrasound images. Therefore, in addition to observing the offset of improving the point spread function, this test can be used to observe how supercompounding handles reflective material layers. Figure 21 is one of the raw images of the metal pin heads. The metal pin heads are arranged as a capital letter 'L'. All images are taken with the 7.5MHz

**Figure 21.** Metal pin heads are arranged as a letter L. The six objects are shown as "T" like shape instead of point like. The axial artifacts are caused by the reverberations inside the metal pin heads. The reverberations mislead the ultra‐ sound imager that there are the same objects in consecutive depths. It makes multiple lines behind the objects. The pin number 1 to 3 and group 4, 5 and 6 are aligned at different depths. The focal zone is 27 millimeter in depth. It is at the middle of the pin number 3 and group 4, 5 and 6; therefore, the pin number 1, 2 and 3 are superficial to the focal

Figure 21 shows artifacts on the image of six objects caused by reverberation. The objects are the metal pin heads and they should appear point like instead of a T-shaped with long tails (reverberations) and wings (side lobes). As stated in section 2.4, the point spread function is space variant in most conventional ultrasound imagers and causes size differences for the same objects depending on how far the object is away from the focal zone. In Figure 21, each pin represents the point spread function at one spatial position. The measurements of di‐

**Pin number Lateral size Axial Size Depth** 46 px 3 px 11.30 mm 31 px 4 px 17.99 mm 11 px 3 px 25.32 mm 13 px 4 px 31.80 mm 13 px 3 px 31.80 mm 13 px 3 px 31.65 mm

linear transducer.

102 Medical Imaging in Clinical Practice

point and the group 4, 5 and 6 are deep to the focal point.

mensions are described in Table 1.

**Table 1.**

The average size in lateral direction is 0.86 ± 0.09 mm and 0.835 ± 0.15 mm in the axial. They are one and half times larger than the actual size of the pin head in all directions. As dis‐ cussed in section 2.5, the supercompounded PSF should be closer to the axial resolution.

#### **4.2. Imaging of dissected porcine aortic root**

The study objects in this section are dissected porcine aortic roots. Each target is scanned un‐ der different pressures and levels (Figure 23), and the images are taken during the inflation test of the aortic root. The inflation test simulates the mechanical response of the aorta under different blood pressure ex-vivo. Different stress levels are simulated when the hydrostatic pressure supply inflates the target.

normal incidence, thus reducing dropout. The entire vessel is symmetrical and intact and spots like echogenicities (arrows in Figure 25) become visible in the supercompounded im‐ age. The supercompounding technique enables the observation and study of these echoge‐

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105

**Figure 25.** Comparison results of the dissected porcine aortic root at aorta level. Region 1 is the superficial area. It is close to the focal zone. It makes the best part of result on the raw image. Region 2 and 3 are the dropout areas. Be‐ cause of the shape of structures in the regions are at the oblique angles to the incident ultrasound waves, the ultra‐ sound waves are not reflected back to the transducer. It makes missing edges on the image. Region 4 is the out of focal zone area. Due to the worse PSF and the attenuation of the ultrasound waves, the structures in the area are not described accurately comparing to the same region on the supercompounded image. In the region 4 of the supercom‐ pounded image, the structures are clear and sharp, but they are blurry and several times larger on the raw image. The

Not only can supercompounding fill the portions of tissues missed by conventional ultra‐ sound imagers, but also can markedly reduce speckle noise in the image. The results shown in Figure 26 and Figure 27 are the aortic roots at leaflets level. Professionally trained eyes might be able to distinguish between an aortic root and the leaflet. Untrained eyes will find

In the raw image Figure 26 (a), the boundary is not clear especially away from the focal zone (region 5 in Figure 27) where is deep to the focal zone of the image. The supercompounded image Figure 26 (b) shows clear edges and details. We can now easily determine the location of the leaflets (region 2, 3 and 4 in Figure 27). The supercompounded image offers a better

arrows point out the echogenicities which are not appeared on the raw image.

it hard to determine the boundaries and the size of the root.

**Figure 26.** The dissected porcine aortic root at leaflets level.

field of view as well, making the image more valuable and easier to read.

nicities and their properties.

**Figure 23.** Illustration of aortic root. The root is scanned at five different levels named aorta, sinotubular junction, leaf‐ lets, sinus and annulus.

The study is focused on the geometry of the aortic valve, which can be used as a standard model to calculate volume changes during the inflation test. The raw images are collect with the 7.5MHz linear transducer. In this research, after derotating and spin averaging the 214 pictures, the resulting supercompounded picture at aorta level is shown in Figure 24 and Figure 25.

The raw B-scan image Figure 24(a) shows sound waves that are dropped-out (region 2 and 3 in Figure 25) at the oblique angles to the normal line of the tissue structure interface. This phenomenon happens when circular shape objects (such as vessels) or spherical objects (such as cysts) are imaged. The supercompounded image (Figure 24(b)), constructed by multi-angular images with an independent viewpoint, exposes each segment of boundary to normal incidence, thus reducing dropout. The entire vessel is symmetrical and intact and spots like echogenicities (arrows in Figure 25) become visible in the supercompounded im‐ age. The supercompounding technique enables the observation and study of these echoge‐ nicities and their properties.

**4.2. Imaging of dissected porcine aortic root**

**Figure 24.** The dissected porcine aortic root at aorta level.

pressure supply inflates the target.

104 Medical Imaging in Clinical Practice

lets, sinus and annulus.

Figure 25.

The study objects in this section are dissected porcine aortic roots. Each target is scanned un‐ der different pressures and levels (Figure 23), and the images are taken during the inflation test of the aortic root. The inflation test simulates the mechanical response of the aorta under different blood pressure ex-vivo. Different stress levels are simulated when the hydrostatic

**Figure 23.** Illustration of aortic root. The root is scanned at five different levels named aorta, sinotubular junction, leaf‐

The study is focused on the geometry of the aortic valve, which can be used as a standard model to calculate volume changes during the inflation test. The raw images are collect with the 7.5MHz linear transducer. In this research, after derotating and spin averaging the 214 pictures, the resulting supercompounded picture at aorta level is shown in Figure 24 and

The raw B-scan image Figure 24(a) shows sound waves that are dropped-out (region 2 and 3 in Figure 25) at the oblique angles to the normal line of the tissue structure interface. This phenomenon happens when circular shape objects (such as vessels) or spherical objects (such as cysts) are imaged. The supercompounded image (Figure 24(b)), constructed by multi-angular images with an independent viewpoint, exposes each segment of boundary to

**Figure 25.** Comparison results of the dissected porcine aortic root at aorta level. Region 1 is the superficial area. It is close to the focal zone. It makes the best part of result on the raw image. Region 2 and 3 are the dropout areas. Be‐ cause of the shape of structures in the regions are at the oblique angles to the incident ultrasound waves, the ultra‐ sound waves are not reflected back to the transducer. It makes missing edges on the image. Region 4 is the out of focal zone area. Due to the worse PSF and the attenuation of the ultrasound waves, the structures in the area are not described accurately comparing to the same region on the supercompounded image. In the region 4 of the supercom‐ pounded image, the structures are clear and sharp, but they are blurry and several times larger on the raw image. The arrows point out the echogenicities which are not appeared on the raw image.

Not only can supercompounding fill the portions of tissues missed by conventional ultra‐ sound imagers, but also can markedly reduce speckle noise in the image. The results shown in Figure 26 and Figure 27 are the aortic roots at leaflets level. Professionally trained eyes might be able to distinguish between an aortic root and the leaflet. Untrained eyes will find it hard to determine the boundaries and the size of the root.

In the raw image Figure 26 (a), the boundary is not clear especially away from the focal zone (region 5 in Figure 27) where is deep to the focal zone of the image. The supercompounded image Figure 26 (b) shows clear edges and details. We can now easily determine the location of the leaflets (region 2, 3 and 4 in Figure 27). The supercompounded image offers a better field of view as well, making the image more valuable and easier to read.

**Figure 26.** The dissected porcine aortic root at leaflets level.

spread function across the ultrasound images. For example, a shadowed region in con‐ ventional ultrasound cannot be restored since the data is simply not present, or the point spread function may obscure fine details beyond the ability of post-processing to retrieve it. Another aspect to consider is that post-processing may be based on preconceived no‐ tions of what certain image regions should look like, thus providing inaccurate informa‐ tion of the imaged anatomy. Consequently, we consider the use of preprocessing techniques to be preferable as they provide "true" improvements in SNR and resolution

Spin Average Supercompound Ultrasonography

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107

**•** A regularized point spread function makes post-processing algorithms [22] (image en‐ hancements) more beneficial to the supercompounded image, especially for linear sys‐ tems algorithms like image deconvolution. By utilizing the two-dimensional spin average theory, supercompounding is shown to improve spatial resolution by having a regular‐ ized and tighter point spread function. Due to space variant resolutions in both axial and lateral directions, the point spread function of ultrasound image changes. Therefore, it is essential to have an ultrasound image with a regularized point spread function for further application of many signal processing algorithms. There is less need to make an assump‐ tion of the space invariant point spread function or to discretize the processed image into

**•** For example, a regularized point spread function can simplify the frequency filtering or deconvolution process which is one of the most straight forward and effective image sharpening methods. As discussed in section 2.1, the obtained image can be modeled as the result of a raw image convolving with a point spread function. This convolution is a blurring process. In order to get back to the original sharp image, the reverse process, namely "deconvolution", is required to restore the image before it convolves with the point spread function. However, it is not directly applicable on ultrasound images be‐ cause of the space variant point spread function. Therefore, the deconvolution is applied regionally or not at all. Since the supercompounded image has a symmetric and regular‐ ized point spread function, the deconvolution process can be applied to the whole image without segmenting it [4, 23, 24]. Thus supercompounding provides a higher quality preprocessed image and also makes post-processing applications more viable and effective.

The results in this study suggest that the spin average concept and the supercompounding technique can dramatically improve the quality of the ultrasound images. The following list

**•** Extremities: The supercompounding applicant could be utilized on extremities. It is easy to gain 360 degrees access around the extremities and usually the ultrasound waves can at least penetrate half of the thickness of the extremities (from superficial skins to the bones in the middle) even with higher frequency ultrasound transducers. It could poten‐ tially be a great way to diagnose and evaluate abnormalities of the muscles and the ten‐

points out three ways to utilize the supercompounding technique in clinically:

small pieces working windows when we process the ultrasound images.

**5.1. Supercompounding applications**

dons, especially for sport medicine.

[22].

**Figure 27.** Comparison results of the dissected porcine aortic root at leaflets level. Region 1 is the area having the best result which is close to the focal zone. Region 2, 3 and 4 are the areas show three leaflets. As the result on the super‐ compounded image, three leaflets appear clearly. However, on the raw image, only the region 4 indicates or suggests a leaflet. The other two in the region 2 and 3 are barely recognized as leaflets. Region 5 is the deep area. It is out of the focal zone. Affected by the worse PSF and the attenuation of the ultrasound waves, the structures are not even close to the real object in the region.

#### **5. Discussions and conclusions**

Supercompounding is an innovative and still developing space compounding technique. It can be applied to traditional ultrasound imaging systems. As shown as this research, the su‐ percompounding technique can provide dramatic improvement to the quality of ultrasonog‐ raphy of typical biologic tissues. The speckle, artifacts and reverberation are reduced, and we are able to visualize complete edges especially at oblique angles to the front of beam di‐ rection. However, these are not the only benefits of supercompounding. By utilizing the two-dimensional spin average theory it was shown that supercompounding can improve spatial resolution by regularizing the point spread function. It is a critical improvement to have an ultrasound image with a regular or space invariant point spread function that can potentially enhance performance by application of linear systems of signal processing algo‐ rithms.

Validation of supercompounding includes two main activities: ultrasound image acquisition and supercompounding processing. Ultrasound image acquisition includes the design and the construction of a three-dimensional moving platform. The platform allows the imaged object to rotate 360 degrees for testing the spin average concept and also to move in three directions for constructing a three-dimensional voxel set of information of the object, a set that could be used to produce a three-dimensional image.

The supercompounding processing has evolved in two sub branches: preprocessing and post-processing algorithms.

**•** Preprocessing technique produces a supercompounded image from derotating and com‐ bining the acquired raw image set. It is considered a preprocessing because the proposed supercompound imaging overcomes some of the physical limitations of ultrasound sig‐ nals. It reduces speckles, shadows and reverberations and gives a regularized point spread function across the ultrasound images. For example, a shadowed region in con‐ ventional ultrasound cannot be restored since the data is simply not present, or the point spread function may obscure fine details beyond the ability of post-processing to retrieve it. Another aspect to consider is that post-processing may be based on preconceived no‐ tions of what certain image regions should look like, thus providing inaccurate informa‐ tion of the imaged anatomy. Consequently, we consider the use of preprocessing techniques to be preferable as they provide "true" improvements in SNR and resolution [22].

#### **5.1. Supercompounding applications**

**Figure 27.** Comparison results of the dissected porcine aortic root at leaflets level. Region 1 is the area having the best result which is close to the focal zone. Region 2, 3 and 4 are the areas show three leaflets. As the result on the super‐ compounded image, three leaflets appear clearly. However, on the raw image, only the region 4 indicates or suggests a leaflet. The other two in the region 2 and 3 are barely recognized as leaflets. Region 5 is the deep area. It is out of the focal zone. Affected by the worse PSF and the attenuation of the ultrasound waves, the structures are not even

Supercompounding is an innovative and still developing space compounding technique. It can be applied to traditional ultrasound imaging systems. As shown as this research, the su‐ percompounding technique can provide dramatic improvement to the quality of ultrasonog‐ raphy of typical biologic tissues. The speckle, artifacts and reverberation are reduced, and we are able to visualize complete edges especially at oblique angles to the front of beam di‐ rection. However, these are not the only benefits of supercompounding. By utilizing the two-dimensional spin average theory it was shown that supercompounding can improve spatial resolution by regularizing the point spread function. It is a critical improvement to have an ultrasound image with a regular or space invariant point spread function that can potentially enhance performance by application of linear systems of signal processing algo‐

Validation of supercompounding includes two main activities: ultrasound image acquisition and supercompounding processing. Ultrasound image acquisition includes the design and the construction of a three-dimensional moving platform. The platform allows the imaged object to rotate 360 degrees for testing the spin average concept and also to move in three directions for constructing a three-dimensional voxel set of information of the object, a set

The supercompounding processing has evolved in two sub branches: preprocessing and

**•** Preprocessing technique produces a supercompounded image from derotating and com‐ bining the acquired raw image set. It is considered a preprocessing because the proposed supercompound imaging overcomes some of the physical limitations of ultrasound sig‐ nals. It reduces speckles, shadows and reverberations and gives a regularized point

that could be used to produce a three-dimensional image.

close to the real object in the region.

106 Medical Imaging in Clinical Practice

post-processing algorithms.

rithms.

**5. Discussions and conclusions**

The results in this study suggest that the spin average concept and the supercompounding technique can dramatically improve the quality of the ultrasound images. The following list points out three ways to utilize the supercompounding technique in clinically:

**•** Extremities: The supercompounding applicant could be utilized on extremities. It is easy to gain 360 degrees access around the extremities and usually the ultrasound waves can at least penetrate half of the thickness of the extremities (from superficial skins to the bones in the middle) even with higher frequency ultrasound transducers. It could poten‐ tially be a great way to diagnose and evaluate abnormalities of the muscles and the ten‐ dons, especially for sport medicine.

**•** Neck: The supercompounding technique could also be used on the neck for diagnosis of carotid atherosclerosis. If plaque builds up in the body's arteries, the condition is called atherosclerosis. Once the built up plaques narrow the common carotid arteries, the pa‐ tient is under a high risk of cerebral flow reduction or stroke because of the reduced blood flow. The diagnosis is often evaluated by CT or multidetector-row CT angiography (CTA) [25] which utilizing ionizing radiation. Supercompounding ultrasound could offer a safer way to make the same diagnosis. The plaque is often calcified which particularly late stage can make it highly reflective. It can show high intensity on the ultrasound im‐ age. Plaques can be identified relatively easily. With the help of the supercompounding technique, the disease could be diagnosed more cost-effective and without exposing pa‐ tients to the ionizing radiations once a proper mechanical supporting apparatus is de‐ signed for 360 degrees scan around the neck.

raw images from the two transducers. This suggests that the resolution of the supercom‐ pounded images is not affected as much as the traditional raw images when we lower the frequencies of the ultrasound transducers. It is potentially a good way of obtaining a satis‐ factory resolution of the supercompounded image with lower frequency transducer without

Spin Average Supercompound Ultrasonography

http://dx.doi.org/10.5772/53238

109

Advances in the technology of transducers, semiconductor devices, and computers have supported the implementation of enhancement techniques and the development of the in‐ dustry of ultrasound in general. The present ultrasound imagers can provide higher signalto-noise ratio and utilize transducer arrays with increasing numbers of elements. Consequently, the quality of the images has improved significantly especially compared to the earlier generation ultrasound imager used in the study (GE RT-3200). However, there has been no major breakthrough from physics point of view. The limitations of ultrasound imaging still remain such as the trade-off between penetration and frequency (resolution), space variant point spread function and sound wave self interference (speckle). These limi‐ tations sometime have become part of the ultrasound imaging, and by well training, radiol‐

If it is possible to obtain higher quality tomographic images of the human body with ultra‐ sound, the use of this technology can be extended to other applications where currently CT and MRI are used and make diagnosis more accurate, safer and more cost-effective for radi‐ ologists or sonographers. The proposed supercompounding imaging of ultrasound is a good approach to make ultrasound imagers perform beyond their present limitations. It works in harmony with the technology of modern ultrasound imagers. Supercompounding will bene‐ fit from better ultrasound transducers. The advantages would be to avoid the exposure of the patients to ionizing radiation and the availability of high quality soft tissue medical imaging at reduced cost. The unique sensitivity of ultrasound to soft tissues also makes it qualitatively superior to X-rays for many applications and it is a much faster modality than magnetic resonance. Overall we feel this technology could provide the impetus for an entire

and Martin Fox3

2 Electrical and Electronic Engineering Program, Universidad Tecnologica de Bolivar, Boli‐

3 Electrical & Computer Engineering, University of Connecticut, Storrs, CT, USA

ogists or sonographers can work around them to some degree.

sacrifice of ultrasound penetration.

new generation of ultrasound imaging.

, Sonia Contreras2

1 Biomedical Engineering, University of Connecticut, Storrs, CT, USA

**Author details**

Tsuicheng D. Chiu1

var, Colombia

**5.2. Conclusions**

**•** Abdomen: Ultrasound imaging is widely used to image certain organs in the abdomen such as the liver, kidneys and pancreas. However, the evaluation is highly related to ex‐ periences and training of the radiologist. For instance, a patient who has liver cancer could have different kind of reports depending on the image reading whether by radiol‐ ogists or other professionals. Imaging can provide information on extend of metastasis of‐ ten diagnosis of cancer is made. Abdominal ultrasound imaging usually is performed with low frequency transducer and has low resolution results. It is radiologists' responsi‐ bilities to discover the abnormalities. With the help of supercompounding, it could reduce the odds for such error. It would be easier for radiologists to identify abnormalities. Ab‐ dominal imaging is made challenging due to the thickness of the belly and the bowels (small and large intestines) which are filled with gas which blocks ultrasound propaga‐ tions. Therefore, ultrasound in the abdomen is limited to a few "windows" where the probe can bypass the intestines and gain access. Even with the 3.5 MHz transducer (which is close to the lowest frequency presently used for ultrasound imaging), it is hard for the ultrasound waves to penetrate through the whole abdomen. There are two possi‐ ble solutions to the task: one is to perform partial supercompounding and the other is to further lower the ultrasound frequency. The partial supercompounding might not help construct an image with complete edges of the object, but it could still be much better than one single raw image according to the spin average concept.

The second solution is to image the abdomen with lower ultrasound frequency such as 1-2MHz. The ultrasound waves might be able to penetrate through; however, the resolution might be worse than using 3.5MHz transducer since for such low frequency, the corre‐ sponding wavelength of sound (at 1MHz) is 154mm, assuming the speed of sound is 1540 m/s in soft tissue. It means the two objects have to be at least 154mm away from each other to be identified as different objects on the ultrasound image when 1MHz transducer is used. Comparing two supercompounded images constructed from raw images scanned by the 7.5MHz and the 3.5 MHz transducers, there is no significant resolution reduction between the two supercompounded images, which is highly noticeable when we compare the two raw images from the two transducers. This suggests that the resolution of the supercom‐ pounded images is not affected as much as the traditional raw images when we lower the frequencies of the ultrasound transducers. It is potentially a good way of obtaining a satis‐ factory resolution of the supercompounded image with lower frequency transducer without sacrifice of ultrasound penetration.

#### **5.2. Conclusions**

**•** Neck: The supercompounding technique could also be used on the neck for diagnosis of carotid atherosclerosis. If plaque builds up in the body's arteries, the condition is called atherosclerosis. Once the built up plaques narrow the common carotid arteries, the pa‐ tient is under a high risk of cerebral flow reduction or stroke because of the reduced blood flow. The diagnosis is often evaluated by CT or multidetector-row CT angiography (CTA) [25] which utilizing ionizing radiation. Supercompounding ultrasound could offer a safer way to make the same diagnosis. The plaque is often calcified which particularly late stage can make it highly reflective. It can show high intensity on the ultrasound im‐ age. Plaques can be identified relatively easily. With the help of the supercompounding technique, the disease could be diagnosed more cost-effective and without exposing pa‐ tients to the ionizing radiations once a proper mechanical supporting apparatus is de‐

**•** Abdomen: Ultrasound imaging is widely used to image certain organs in the abdomen such as the liver, kidneys and pancreas. However, the evaluation is highly related to ex‐ periences and training of the radiologist. For instance, a patient who has liver cancer could have different kind of reports depending on the image reading whether by radiol‐ ogists or other professionals. Imaging can provide information on extend of metastasis of‐ ten diagnosis of cancer is made. Abdominal ultrasound imaging usually is performed with low frequency transducer and has low resolution results. It is radiologists' responsi‐ bilities to discover the abnormalities. With the help of supercompounding, it could reduce the odds for such error. It would be easier for radiologists to identify abnormalities. Ab‐ dominal imaging is made challenging due to the thickness of the belly and the bowels (small and large intestines) which are filled with gas which blocks ultrasound propaga‐ tions. Therefore, ultrasound in the abdomen is limited to a few "windows" where the probe can bypass the intestines and gain access. Even with the 3.5 MHz transducer (which is close to the lowest frequency presently used for ultrasound imaging), it is hard for the ultrasound waves to penetrate through the whole abdomen. There are two possi‐ ble solutions to the task: one is to perform partial supercompounding and the other is to further lower the ultrasound frequency. The partial supercompounding might not help construct an image with complete edges of the object, but it could still be much better

than one single raw image according to the spin average concept.

The second solution is to image the abdomen with lower ultrasound frequency such as 1-2MHz. The ultrasound waves might be able to penetrate through; however, the resolution might be worse than using 3.5MHz transducer since for such low frequency, the corre‐ sponding wavelength of sound (at 1MHz) is 154mm, assuming the speed of sound is 1540 m/s in soft tissue. It means the two objects have to be at least 154mm away from each other to be identified as different objects on the ultrasound image when 1MHz transducer is used. Comparing two supercompounded images constructed from raw images scanned by the 7.5MHz and the 3.5 MHz transducers, there is no significant resolution reduction between the two supercompounded images, which is highly noticeable when we compare the two

signed for 360 degrees scan around the neck.

108 Medical Imaging in Clinical Practice

Advances in the technology of transducers, semiconductor devices, and computers have supported the implementation of enhancement techniques and the development of the in‐ dustry of ultrasound in general. The present ultrasound imagers can provide higher signalto-noise ratio and utilize transducer arrays with increasing numbers of elements. Consequently, the quality of the images has improved significantly especially compared to the earlier generation ultrasound imager used in the study (GE RT-3200). However, there has been no major breakthrough from physics point of view. The limitations of ultrasound imaging still remain such as the trade-off between penetration and frequency (resolution), space variant point spread function and sound wave self interference (speckle). These limi‐ tations sometime have become part of the ultrasound imaging, and by well training, radiol‐ ogists or sonographers can work around them to some degree.

If it is possible to obtain higher quality tomographic images of the human body with ultra‐ sound, the use of this technology can be extended to other applications where currently CT and MRI are used and make diagnosis more accurate, safer and more cost-effective for radi‐ ologists or sonographers. The proposed supercompounding imaging of ultrasound is a good approach to make ultrasound imagers perform beyond their present limitations. It works in harmony with the technology of modern ultrasound imagers. Supercompounding will bene‐ fit from better ultrasound transducers. The advantages would be to avoid the exposure of the patients to ionizing radiation and the availability of high quality soft tissue medical imaging at reduced cost. The unique sensitivity of ultrasound to soft tissues also makes it qualitatively superior to X-rays for many applications and it is a much faster modality than magnetic resonance. Overall we feel this technology could provide the impetus for an entire new generation of ultrasound imaging.

#### **Author details**

Tsuicheng D. Chiu1 , Sonia Contreras2 and Martin Fox3

1 Biomedical Engineering, University of Connecticut, Storrs, CT, USA

2 Electrical and Electronic Engineering Program, Universidad Tecnologica de Bolivar, Boli‐ var, Colombia

3 Electrical & Computer Engineering, University of Connecticut, Storrs, CT, USA

#### **References**

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[16] J. R. Jago and T. A. Whittingham, "Experimental Studies in Transmission Ultrasound Computed Tomography," Physics in Medicine and Biology, vol. 36, pp. 1515-1527,

Spin Average Supercompound Ultrasonography

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111

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**Chapter 6**

**Ocular Movement and Cardiac Rhythm Control using**

There exist different methods to analyze and study biomedical signals. Some of these methods are based on medical imaging, involving Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Nuclear Scintigraphy, etc. This techniques show the image of a specific part of the human body. But there exits other methods which study the different signals based in 1-dimensional analysis, such as Electroencephalography (EEG), Electrocardiography (ECG),

These techniques are not only used to detect any anomaly, but in the case of the EEG, it is also possible to develop communication systems by Brain Computer Interface (BCI) [1]. The BCI technology has numerous applications which can improve the quality of life of those people who need external help at the time of communication or controlling their movements.

EEG records the electrical activity along the scalp produced by the neurons. This activity happens since the brain cells communicate each other giving place to tiny electrical impulses.

The impulse begins with a chemical discharge which origins a current in the membrane of the emitting cell. Once the impulse gets the extreme of the connection between cells, the neuron

After receiving the signal, the neuron releases ions to the outside of the cell. When lots of ions are expelled at the same time they can stimulate other neurons. At the time this wave of ions gets to the electrodes, the ions can attract or push the metal of the electrodes. This difference of pressure can be measured by a voltmeter and the record of this activity along time is the

and reproduction in any medium, provided the original work is properly cited.

© 2013 Viqueira et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

etc. These do not show an image, but they also show relevant information.

secretes a protein that inhibits or excites another neuron.

**EEG Techniques**

Amaia Mendez Zorrilla

http://dx.doi.org/10.5772/55375

**1. Introduction**

EEG signal.

María Viqueira, Begoña García Zapirain and

Additional information is available at the end of the chapter

## **Ocular Movement and Cardiac Rhythm Control using EEG Techniques**

María Viqueira, Begoña García Zapirain and Amaia Mendez Zorrilla

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/55375

#### **1. Introduction**

There exist different methods to analyze and study biomedical signals. Some of these methods are based on medical imaging, involving Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Nuclear Scintigraphy, etc. This techniques show the image of a specific part of the human body. But there exits other methods which study the different signals based in 1-dimensional analysis, such as Electroencephalography (EEG), Electrocardiography (ECG), etc. These do not show an image, but they also show relevant information.

These techniques are not only used to detect any anomaly, but in the case of the EEG, it is also possible to develop communication systems by Brain Computer Interface (BCI) [1]. The BCI technology has numerous applications which can improve the quality of life of those people who need external help at the time of communication or controlling their movements.

EEG records the electrical activity along the scalp produced by the neurons. This activity happens since the brain cells communicate each other giving place to tiny electrical impulses.

The impulse begins with a chemical discharge which origins a current in the membrane of the emitting cell. Once the impulse gets the extreme of the connection between cells, the neuron secretes a protein that inhibits or excites another neuron.

After receiving the signal, the neuron releases ions to the outside of the cell. When lots of ions are expelled at the same time they can stimulate other neurons. At the time this wave of ions gets to the electrodes, the ions can attract or push the metal of the electrodes. This difference of pressure can be measured by a voltmeter and the record of this activity along time is the EEG signal.

© 2013 Viqueira et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

**Figure 1.** EEG operation

Different studies show that, with the correct training, it is possible to control different external devices with the BCI technology. In [2], Galán et al. present a study where two users have to control a wheelchair using a system based in BCI. They have concluded that the success has been higher after learning the interaction with the system.

The electrooculography (EOG) is based on the electrical activity of the eyes movement and it has been used for the user's communication. There are other applications based on the eye movements to control devices. They detect the user's iris, so it can know the position the user is looking through the coordinates of the iris. In [6] the study presents a method to control a wheelchair with one camera establishing three points as reference: the eyes and the nose. This

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The ECG is a register of the electrical activity of the heart in order to know if there is any

**•** Bipolar placement: each channel represents the difference between two adjacent electrodes.

**•** Referential or monopolar placement: each channel represents the difference between one electrode and another one established as reference. The ECG has been acquired with this

The chosen electrodes are adhesive because of their facility to be placed both in the face as well

The electrodes are responsible for registering the voltage inside a single cell. An electric impulse, known as the action potential, is an electric discharge which travels along the cellular membrane. The action potential is used to transport the information between the tissues. Although they can be generated for different kind of corporal cells, the most active are the cells

three points form a triangle.

**Figure 3.** PET 4.0: EEG of 4 channels

montage.

of the nervous system [7].

anomaly depending on the heart behavior.

This montage has been used for the EOG.

We have used two different placements of the electrodes:

as in the breast. The diameter of each electrode is 24 millimeters.

**Figure 4.** Kendall Arbo electrodes. Source: http://www.brainquiry.com/KendallArbo.html

With respect to the communication, the most used technique is the detection of the P300 wave as result of a photostimulus [3]. In these cases, the user has to watch one keyboard where the columns and rows are illuminated randomly. If the letter the person is watching is illuminated, the brain sends a signal as a response to that photostimulus. This answer is called P300.

**Figure 2.** Keyboard used for the detection of P300. Source: http://www.bbci.de/competition/ii/albany\_desc/alba‐ ny\_desc\_ii.html

In [4] the authors use a system based on evoked potential to control one robotic arm. The system illuminates different actions which can be made by the arm. To know which action the user is focused, they detect the P300 and the N2pc.

There are also different applications of BCI technology in different games, such as Mindball [5], which consist on moving a ball depending on the brain activity: the more relaxed and focused the user is, the more the ball will move.

But electrodes are not only used to measure brain signals, but they also register the electrical activity from other parts, such as the heart (ECG) or the skeletal muscles (EMG). It is also possible to pick up the muscular activity, as it could be the measurement of the eye movements (EOG).

We have decided to use an EEG as electrocardiograph (ECG) and as electrooculography (EOG). The used device is the same for both applications: a portable EEG with 4 different channels.

This device was initially acquired to work in one application in which it was necessary to carry a portable EEG. Due to its portability, it can collect data during long periods of time and outdoors.

**Figure 3.** PET 4.0: EEG of 4 channels

**Figure 1.** EEG operation

114 Medical Imaging in Clinical Practice

ny\_desc\_ii.html

(EOG).

outdoors.

Different studies show that, with the correct training, it is possible to control different external devices with the BCI technology. In [2], Galán et al. present a study where two users have to control a wheelchair using a system based in BCI. They have concluded that the success has

With respect to the communication, the most used technique is the detection of the P300 wave as result of a photostimulus [3]. In these cases, the user has to watch one keyboard where the columns and rows are illuminated randomly. If the letter the person is watching is illuminated, the brain sends a signal as a response to that photostimulus. This answer is called P300.

**Figure 2.** Keyboard used for the detection of P300. Source: http://www.bbci.de/competition/ii/albany\_desc/alba‐

In [4] the authors use a system based on evoked potential to control one robotic arm. The system illuminates different actions which can be made by the arm. To know which action the user is

There are also different applications of BCI technology in different games, such as Mindball [5], which consist on moving a ball depending on the brain activity: the more relaxed and

But electrodes are not only used to measure brain signals, but they also register the electrical activity from other parts, such as the heart (ECG) or the skeletal muscles (EMG). It is also possible to pick up the muscular activity, as it could be the measurement of the eye movements

We have decided to use an EEG as electrocardiograph (ECG) and as electrooculography (EOG). The used device is the same for both applications: a portable EEG with 4 different channels.

This device was initially acquired to work in one application in which it was necessary to carry a portable EEG. Due to its portability, it can collect data during long periods of time and

been higher after learning the interaction with the system.

focused, they detect the P300 and the N2pc.

focused the user is, the more the ball will move.

The electrooculography (EOG) is based on the electrical activity of the eyes movement and it has been used for the user's communication. There are other applications based on the eye movements to control devices. They detect the user's iris, so it can know the position the user is looking through the coordinates of the iris. In [6] the study presents a method to control a wheelchair with one camera establishing three points as reference: the eyes and the nose. This three points form a triangle.

The ECG is a register of the electrical activity of the heart in order to know if there is any anomaly depending on the heart behavior.

We have used two different placements of the electrodes:

The chosen electrodes are adhesive because of their facility to be placed both in the face as well as in the breast. The diameter of each electrode is 24 millimeters.

**Figure 4.** Kendall Arbo electrodes. Source: http://www.brainquiry.com/KendallArbo.html

The electrodes are responsible for registering the voltage inside a single cell. An electric impulse, known as the action potential, is an electric discharge which travels along the cellular membrane. The action potential is used to transport the information between the tissues. Although they can be generated for different kind of corporal cells, the most active are the cells of the nervous system [7].

But to register the eye activity it is not necessary to place the electrodes on the head, it can be

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An EOG is a method to register the eyes movement by placing little electrodes near the eyes muscles. Under normal conditions there exists a potential difference (10μV to 5 mV approxi‐ mately) between the cornea and the Bruch´s membrane, located on the back of the eye. This is known as cornea-retinal potential. The cornea corresponds to the positive extreme and the

In [8] it is well explained the different kinds of eye tracking systems and the evolution of them. For studying the eyes movement the criteria for divide the different techniques is different.

Figure 7 represents the differential of potential between the cornea and the retina:

registered placing the electrodes in the face, which is called EOG.

retina corresponds to the negative of the dipole.

Figure 8 show the behavior of the eye as a dipole:

**Figure 7.** Cornea - retinal potential

**Figure 8.** Eyes movement potential

There are three different kinds of eye tracking:

For the monitoring and the posterior analysis we have developed two user's interface in Matlab: one for the ECG and another one for the EOG.

#### **2. Relation between EEG and EOG**

During the register of an EEG, there can appear different signals called artifacts. These signals can be originated by multiple causes: muscular movements, skin impedance, technical problems, etc. One of the causes of these artifacts can be the ocular movement, such as eye blinking. This electrical activity is registered in the frontal region of the brain, being FP1, FP2 the channels where can best be appreciable.

**Figure 6.** EEG with two eye blinking

But to register the eye activity it is not necessary to place the electrodes on the head, it can be registered placing the electrodes in the face, which is called EOG.

 Under normal conditions there exists a potential difference (10μV to 5 mV approxi‐ mately) between the cornea and the Bruch´s membrane, located on the back of the eye. This is known as cornea-retinal potential. The cornea corresponds to the positive extreme and the retina corresponds to the negative of the dipole.

Figure 7 represents the differential of potential between the cornea and the retina:

**Figure 7.** Cornea - retinal potential

**Figure 5.** Action potential

116 Medical Imaging in Clinical Practice

Matlab: one for the ECG and another one for the EOG.

**2. Relation between EEG and EOG**

the channels where can best be appreciable.

**Figure 6.** EEG with two eye blinking

For the monitoring and the posterior analysis we have developed two user's interface in

During the register of an EEG, there can appear different signals called artifacts. These signals can be originated by multiple causes: muscular movements, skin impedance, technical problems, etc. One of the causes of these artifacts can be the ocular movement, such as eye blinking. This electrical activity is registered in the frontal region of the brain, being FP1, FP2 Figure 8 show the behavior of the eye as a dipole:

**Figure 8.** Eyes movement potential

In [8] it is well explained the different kinds of eye tracking systems and the evolution of them. For studying the eyes movement the criteria for divide the different techniques is different. There are three different kinds of eye tracking:

**•** Invasive technique: this technique uses a special contact lens with an incorporated mirror or a magnetic field senor. The data acquired are more detailed because it is in contact with the eyeball, but is more uncomfortable because the user has to wear the contact lens.

The final application will have one user interface divided into two tasks:

**•** Interpret what the user wants to express.

**Figure 11.** User's interface of EOG

**Figure 12.** Keyboard

**•** Communicate between the device and the main application via Bluetooth.

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For the first task, we have used the API provided by the fabricant. To allow the user's com‐

The user moves one circle through the keyboard by moving his eyes to the left, to the right, up or down. Once the user selects "OK", the application will use the T9 dictionary to interpret the correct word. The dictionary has been programmed taking in count the words which meaning

Figure 13 show the difference between looking up and looking down. The subtraction of CH2

munication, the application will show the same keyboard as Figure 12:

is related with expressing feelings and emotional states.

and CH3 accentuates the difference between the eye movements.

#### **Figure 9.** Purkinge images

The montage of the electrodes is bipolar: we register the difference between two electrodes. As the device is a 4 channel EEG, we have used them to perform 2 different positions: one for register if the user is looking on the left or on the right; and a second one to check if the user is looking up or down. The reference electrodes are placed in the ears.

**Figure 10.** Electrodes position of EOG

The difference between channels 2 and 3 shows whether the user is looking up (positive) or down (negative). The difference between channels 4 and 5 determines if the user has looked to the left (positive) or to the right (negative).

The final application will have one user interface divided into two tasks:

**•** Invasive technique: this technique uses a special contact lens with an incorporated mirror or a magnetic field senor. The data acquired are more detailed because it is in contact with the eyeball, but is more uncomfortable because the user has to wear the contact lens. **•** Electrical potential: it uses electrodes placed around the eyes to detect the movement [9]. It is a robust method to measure the ocular movements when there are eyes blinking or change of the gaze. The main disadvantage is that it may become uncomfortable and the register can be affected by the electrodes movement. One of the main advantages is that it registers the eye movement with closed eyes so they can be used in the analysis of sleeping problems

**•** Non - invasive technique: there is no contact with the eyes. The eyes movement is located through a camera or an optical sensor. The infrared light generates different reflections of

The montage of the electrodes is bipolar: we register the difference between two electrodes. As the device is a 4 channel EEG, we have used them to perform 2 different positions: one for register if the user is looking on the left or on the right; and a second one to check if the user

The difference between channels 2 and 3 shows whether the user is looking up (positive) or down (negative). The difference between channels 4 and 5 determines if the user has looked

[10] and [11]. The EOG is within this kind of eye tracking.

**Figure 9.** Purkinge images

118 Medical Imaging in Clinical Practice

**Figure 10.** Electrodes position of EOG

to the left (positive) or to the right (negative).

the cornea of the user's eyes known as Purkinje images [12] and [13].

is looking up or down. The reference electrodes are placed in the ears.

**Figure 11.** User's interface of EOG

For the first task, we have used the API provided by the fabricant. To allow the user's com‐ munication, the application will show the same keyboard as Figure 12:

#### **Figure 12.** Keyboard

The user moves one circle through the keyboard by moving his eyes to the left, to the right, up or down. Once the user selects "OK", the application will use the T9 dictionary to interpret the correct word. The dictionary has been programmed taking in count the words which meaning is related with expressing feelings and emotional states.

Figure 13 show the difference between looking up and looking down. The subtraction of CH2 and CH3 accentuates the difference between the eye movements.

In order to synchronize the cyclical contraction of the heart, the fibers of the cardiac muscle

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The electrical activity is the potential difference generated by the cardiac cells (each cell acts as a voltage generator) which are appreciable on the skin surface, where the electrodes pick

"P Wave": the cardiac cycle begins with the depolarization, which leads on the contraction of the atriums in order to deposit the blood in the ventricles. The sinus node (SA node) indi‐ cates the atrium muscles that they have to contract to begin the sequence. The potential ac‐ tion is propagated through the specialized cells of the cardiac muscle to the AV nodule.

"QRS complex": the wave of depolarization arrives to the ventricles through the Bundle of His

"ST segment": indicates the time between the end of the contraction of the ventricles and the

and the Purkinje fibers, producing the contraction of the ventricles.

transmit electrical impulses.

**Figure 15.** Atrial systole

**Figure 16.** QRS complex

beginning of the resting period.

up this activity in order to get a graphical representation.

This representation shows 4 significant parts:

**Figure 13.** Difference between looking up and down

In Figure 14, which shows the difference between looking to the left or to the right, it can be seen that the situation is similar than looking up and down: looking to the left produces an increment of the signal value, while looking to the right decrements it.

**Figure 14.** Difference between looking to the left and to the right

#### **3. Relation between EEG and ECG**

An ECG is the graphical representation of the electrical activity precedent from the heart. It is a non - invasive method to study and to analyse the condition of the heart with the aim of detecting possible anomalies or diseases.

In order to synchronize the cyclical contraction of the heart, the fibers of the cardiac muscle transmit electrical impulses.

The electrical activity is the potential difference generated by the cardiac cells (each cell acts as a voltage generator) which are appreciable on the skin surface, where the electrodes pick up this activity in order to get a graphical representation.

This representation shows 4 significant parts:

"P Wave": the cardiac cycle begins with the depolarization, which leads on the contraction of the atriums in order to deposit the blood in the ventricles. The sinus node (SA node) indi‐ cates the atrium muscles that they have to contract to begin the sequence. The potential ac‐ tion is propagated through the specialized cells of the cardiac muscle to the AV nodule.

**Figure 15.** Atrial systole

**Figure 13.** Difference between looking up and down

120 Medical Imaging in Clinical Practice

**Figure 14.** Difference between looking to the left and to the right

**3. Relation between EEG and ECG**

detecting possible anomalies or diseases.

In Figure 14, which shows the difference between looking to the left or to the right, it can be seen that the situation is similar than looking up and down: looking to the left produces an

An ECG is the graphical representation of the electrical activity precedent from the heart. It is a non - invasive method to study and to analyse the condition of the heart with the aim of

increment of the signal value, while looking to the right decrements it.

"QRS complex": the wave of depolarization arrives to the ventricles through the Bundle of His and the Purkinje fibers, producing the contraction of the ventricles.

**Figure 16.** QRS complex

"ST segment": indicates the time between the end of the contraction of the ventricles and the beginning of the resting period.

When the electrical impulse arrives to a cardiac cell it provokes the interchange of ions inside the cell, giving place to a change of polarity. The action potential is the base for the depolari‐ zation and polarization of the myocardium: it is what generates the electrical impulse.

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The electrodes are places along the trunk of the users, taking the shoulders as reference. Figure

The user's interface has the aspect of Figure 22. The user can select the channels in both graphs.

21 shows the position of the electrodes for the correct register of the ECG.

**Figure 20.** Cardiac action potential

**Figure 21.** Electrodes placement

"T wave": indicates the repolarization of the ventricles.

**Figure 18.** T wave

Figure 19 is the representation of a normal ECG. There can be appreciated the different waves explained before.

**Figure 19.** Heart signals

When the electrical impulse arrives to a cardiac cell it provokes the interchange of ions inside the cell, giving place to a change of polarity. The action potential is the base for the depolari‐ zation and polarization of the myocardium: it is what generates the electrical impulse.

**Figure 20.** Cardiac action potential

**Figure 17.** ST segment

122 Medical Imaging in Clinical Practice

**Figure 18.** T wave

explained before.

**Figure 19.** Heart signals

"T wave": indicates the repolarization of the ventricles.

Figure 19 is the representation of a normal ECG. There can be appreciated the different waves

The electrodes are places along the trunk of the users, taking the shoulders as reference. Figure 21 shows the position of the electrodes for the correct register of the ECG.

The user's interface has the aspect of Figure 22. The user can select the channels in both graphs.

Once the application shows the keyboard, it will do the operations described in Figure 24 and

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The signal is obtained during 200ms and then the application calculates the average during this time interval. After that, it compares if there has been an enough increment or decrement

Figure 26 and Figure 27 show the calibration state of the EOG before showing the keyboard. The first two images correspond to looing up (yellow rectangle) and down (green rectangle).

Figure 25 to know if the user has made any action with the eyes.

**Figure 24.** Up and down criterion

**Figure 25.** Left and right criterion

to detect if the user has moved the eyes intentionally.

**Figure 22.** User's interface for ECG

#### **4. Practice examples**

#### **4.1. EOG**

In this section, it will be described how the EOG has been used to move a mark along a keyboard on the screen in order to help the people who are not able to communicate with the rest due a disease.

First of all, the application calibrates the position of the electrodes and establishes the corre‐ spondent thresholds to know the position of the eyes. After that, it will show the keyboard the user will use for the communication.

**Figure 23.** General diagram

Once the application shows the keyboard, it will do the operations described in Figure 24 and Figure 25 to know if the user has made any action with the eyes.

**Figure 24.** Up and down criterion

**Figure 22.** User's interface for ECG

124 Medical Imaging in Clinical Practice

**4. Practice examples**

In this section, it will be described how the EOG has been used to move a mark along a keyboard on the screen in order to help the people who are not able to communicate with the

First of all, the application calibrates the position of the electrodes and establishes the corre‐ spondent thresholds to know the position of the eyes. After that, it will show the keyboard the

**4.1. EOG**

rest due a disease.

**Figure 23.** General diagram

user will use for the communication.

The signal is obtained during 200ms and then the application calculates the average during this time interval. After that, it compares if there has been an enough increment or decrement to detect if the user has moved the eyes intentionally.

**Figure 25.** Left and right criterion

Figure 26 and Figure 27 show the calibration state of the EOG before showing the keyboard. The first two images correspond to looing up (yellow rectangle) and down (green rectangle).

After acquiring the signal (Figure 29), it is filtered with a Butterworth bandpass filter between

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Once the signal has been filtered, we have established a threshold to facilitate the detection of

15Hz and 50Hz to detect the QRS complex (Figure 30).

**Figure 29.** Original ECG

**Figure 30.** Butterworth filter

the R wave (Figure 31):

**Figure 26.** Looking up and down

Below, the pictures show the user looking to the left (dark blue) or to the right (cyan).

**Figure 27.** Looking to the left and to the right

The EOG has been tested with 5 different users (3 female, 2 male) with ages between 23 and 30. They have been asked to spell 5 different words: WATER, FISH, SUN, DOG and MIND.

#### **4.2. ECG**

This section describes the ECG used to monitor the heart activity and to detect possible anomalies. In this case, the montage is monopolar, so we can obtain information from 4 different points (4 channels), establishing as a reference the user's shoulders. The signals the ECG records are smoothed before being monitored.

**Figure 28.** General diagram of ECG monitoring

After acquiring the signal (Figure 29), it is filtered with a Butterworth bandpass filter between 15Hz and 50Hz to detect the QRS complex (Figure 30).

**Figure 29.** Original ECG

**Figure 26.** Looking up and down

126 Medical Imaging in Clinical Practice

**Figure 27.** Looking to the left and to the right

**Figure 28.** General diagram of ECG monitoring

ECG records are smoothed before being monitored.

**4.2. ECG**

Below, the pictures show the user looking to the left (dark blue) or to the right (cyan).

The EOG has been tested with 5 different users (3 female, 2 male) with ages between 23 and 30. They have been asked to spell 5 different words: WATER, FISH, SUN, DOG and MIND.

This section describes the ECG used to monitor the heart activity and to detect possible anomalies. In this case, the montage is monopolar, so we can obtain information from 4 different points (4 channels), establishing as a reference the user's shoulders. The signals the

**Figure 30.** Butterworth filter

Once the signal has been filtered, we have established a threshold to facilitate the detection of the R wave (Figure 31):

Table 2 contains the average of each word by letter and by users. The number inside the parenthesis indicates the total number of letters of each word involving the five sessions (five

WATER (25) 100% 100% FISH (20) 65% 40% SUN (15) 100% 100% DOG (15) 100% 100% MIND (15) 90% 80%

After establishing different thresholds, it is possible to select the wished letter controlling the

Figure 32 and Figure 33 present the different movements for the spelling of the words DOG

**Average by letters Average by users**

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different users).

**Table 2.** Average of each word

**Figure 32.** Eye movements for the word DOG

and WATER respectively.

movement with the eyes with an average of the 90.53%.

**Figure 31.** Signal after establishing the threshold

*if data* (*i*) < 2\**average* – *data* (*i*) = 0

#### **5. Results**

#### **5.1. EOG**

We have asked the users to move a circle along a keyboard to spell five different words. We have divided the results into areas: the spelling of the whole word and the spelling of the single letters.

It has been established that if the user expends more than three attempts to move the mark, the objective letter is considered as an error.

Table 1 shows the obtained results for the different users:

**Table 1.** Spelled words by users

Table 2 contains the average of each word by letter and by users. The number inside the parenthesis indicates the total number of letters of each word involving the five sessions (five different users).

**Table 2.** Average of each word

**Figure 31.** Signal after establishing the threshold

the objective letter is considered as an error.

**Table 1.** Spelled words by users

Table 1 shows the obtained results for the different users:

We have asked the users to move a circle along a keyboard to spell five different words. We have divided the results into areas: the spelling of the whole word and the spelling of the single

It has been established that if the user expends more than three attempts to move the mark,

WATER o o o o o FISH x o x x o SUN o o o o o DOG o o o o o MIND o o x o o Average letter 78.95% 100% 84.21% 89.47 100% Average word 80% 100% 60% 80% 100%

**User 1 User 2 User 3 User 4 User 5**

*if data* (*i*) < 2\**average* – *data* (*i*) = 0

128 Medical Imaging in Clinical Practice

**5. Results**

**5.1. EOG**

letters.

After establishing different thresholds, it is possible to select the wished letter controlling the movement with the eyes with an average of the 90.53%.

**Figure 32.** Eye movements for the word DOG

Figure 32 and Figure 33 present the different movements for the spelling of the words DOG and WATER respectively.

**Figure 33.** Eye movements for the word WATER

The following two graphs are presented where the word FISH is correctly spelled (Figure 34) and wrongly spelled (Figure 35).

**Figure 35.** Word FISH bad spelled

The ECG allows the detection of the principal waves for the posterior analysis of anomalies.

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The ECG shown in Figure 37 presents a premature ventricular contraction after the T wave.

**5.2. ECG**

**Figure 36.** Normal ECG

**Figure 34.** Word FISH well spelled

It can be seen that an exception has happened with the EOG at the time the user was spelling fish.

**Figure 35.** Word FISH bad spelled

#### **5.2. ECG**

**Figure 33.** Eye movements for the word WATER

130 Medical Imaging in Clinical Practice

34) and wrongly spelled (Figure 35).

**Figure 34.** Word FISH well spelled

The following two graphs are presented where the word FISH is correctly spelled (Figure

It can be seen that an exception has happened with the EOG at the time the user was spelling fish.

The ECG allows the detection of the principal waves for the posterior analysis of anomalies.

**Figure 36.** Normal ECG

The ECG shown in Figure 37 presents a premature ventricular contraction after the T wave.

The three graphs explained above correspond to three different users, showing the channels acquired for the 4 electrodes. The first one presents a normal ECG while the other two present

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Comparing the normal ECG with the rest, it can be seen that there are differences between the form of the wave and the RR intervals. In the second graph, there is a beat which is advanced in respect of a normal frequency. Because of that, the second graph presents few numbers of

Regarding to the third graph, the form of the waves is similar than the normal ECG, but the heart frequency is not constant: it can be appreciated that the heart frequency is not constant

As it has been demonstrated, the sensors used in BCI have an extra potential for applications

The signals recorded by an EEG, an EOG and an ECG are bioelectrical signals; that is why the techniques to obtain the electrical activity of the brain, the eye movements and the heart activity are very similar. In the three cases, it is necessary to place electrodes in order to measure the

The electrical activity of the eyes and the heart movement can be better appreciated than the activity from the brain. Because of that, it has been possible to use one EEG device as ECG and EOG as the resolution to distinguish the different signals is less than in an EEG. On the contrary,

The election of the type of electrodes that are needed to be used is very important depending on the signal to measure and the needed resolution. The chosen electrodes are good for the recording of an EOG and an ECG, but their resolution may not be sufficient in some EEG

Regarding to the EOG, the users have communicated the different letters with an average of 90.53%. With the appropriate training, the times of spelling could be reduced and it would be

**•** Improve the results of the EOG adding new functions to the interface and check the most

it could be not possible to use as EEG a device which has not been designed for that.

**•** Use the EEG for analyzing more bioelectrical signals, for example EMG.

**•** Analyze the signals in real time in order to detect any possible anomaly.

adequate trainings to increase the percentage of success.

two kinds of anomalies: premature ventricular contraction and arrhythmia.

RR intervals (6 beats in 10 seconds).

**6. Conclusions**

biologic potentials.

applications.

possible to increase the hit rate.

As future work there could be three different lines:

which need high sensitivity.

due to a little pause between the seconds 83 and 86.

**Figure 37.** ECG for different channels with anomaly

Figure 38 contains an ECG with arrhythmias: the cardiac frequency presents an alteration in the second 83 and the second 86.

**Figure 38.** ECG for different channels with arrhythmias

The three graphs explained above correspond to three different users, showing the channels acquired for the 4 electrodes. The first one presents a normal ECG while the other two present two kinds of anomalies: premature ventricular contraction and arrhythmia.

Comparing the normal ECG with the rest, it can be seen that there are differences between the form of the wave and the RR intervals. In the second graph, there is a beat which is advanced in respect of a normal frequency. Because of that, the second graph presents few numbers of RR intervals (6 beats in 10 seconds).

Regarding to the third graph, the form of the waves is similar than the normal ECG, but the heart frequency is not constant: it can be appreciated that the heart frequency is not constant due to a little pause between the seconds 83 and 86.

#### **6. Conclusions**

**Figure 37.** ECG for different channels with anomaly

**Figure 38.** ECG for different channels with arrhythmias

the second 83 and the second 86.

132 Medical Imaging in Clinical Practice

Figure 38 contains an ECG with arrhythmias: the cardiac frequency presents an alteration in

As it has been demonstrated, the sensors used in BCI have an extra potential for applications which need high sensitivity.

The signals recorded by an EEG, an EOG and an ECG are bioelectrical signals; that is why the techniques to obtain the electrical activity of the brain, the eye movements and the heart activity are very similar. In the three cases, it is necessary to place electrodes in order to measure the biologic potentials.

The electrical activity of the eyes and the heart movement can be better appreciated than the activity from the brain. Because of that, it has been possible to use one EEG device as ECG and EOG as the resolution to distinguish the different signals is less than in an EEG. On the contrary, it could be not possible to use as EEG a device which has not been designed for that.

The election of the type of electrodes that are needed to be used is very important depending on the signal to measure and the needed resolution. The chosen electrodes are good for the recording of an EOG and an ECG, but their resolution may not be sufficient in some EEG applications.

Regarding to the EOG, the users have communicated the different letters with an average of 90.53%. With the appropriate training, the times of spelling could be reduced and it would be possible to increase the hit rate.

As future work there could be three different lines:

#### **Acknowledgements**

Finally, we would like to thank to those people who has helped to develop the application, especially to Eneko Lopetegui, because his advices and knowledge.

[10] Liang, S-F, Chen, Y-H, Kuo, C-E, Chen, J-Y, & Hsu, S-C. A fuzzy inference system for sleep staging. In: 2011 IEEE International Conference on Fuzzy Systems. Taipei, Tai‐

Ocular Movement and Cardiac Rhythm Control using EEG Techniques

http://dx.doi.org/10.5772/55375

135

[11] Tagluk, M. E, Sezgin, N, & Akin, M. Estimation of sleep stages by an artificial neural network employing EEG, EMG and EOG. Journal of medical systems. (2010). Aug; ,

[12] Talukder, A, Morookian, J, Monacos, S, Lam, R, Lebaw, C, & Bond, A. Real-time Non-Invasive Eyetracking and Gaze-point Determination for Human-Computer In‐ teraction and Biomedicine. In: SPIE Defense and Security Symposioum, Optical Pat‐

[13] Weigle, C, & Banks, D. C. Analysis of eye-tracking experiments performed on a Tobii T60. In: Woods AJ, McDowall IE, Corner BD, Rogowitz BE, Börner K, Eschbach R, et al., editors. Proceedings of the SPIE. Visualization and Data Analysis. San José, CA,

tern Recognition. Orlando, FL, United States, April 12-16, (2004).

wan, June 27- 30: (2011). , 2104-2107.

United States, January 28- 29, (2008).

34(4), 717-25.

#### **Author details**

María Viqueira, Begoña García Zapirain and Amaia Mendez Zorrilla

Deustotech-LIFE, Universidad de Deusto, Bilbao, Spain

#### **References**

[10] Liang, S-F, Chen, Y-H, Kuo, C-E, Chen, J-Y, & Hsu, S-C. A fuzzy inference system for sleep staging. In: 2011 IEEE International Conference on Fuzzy Systems. Taipei, Tai‐ wan, June 27- 30: (2011). , 2104-2107.

**Acknowledgements**

134 Medical Imaging in Clinical Practice

**Author details**

**References**

Finally, we would like to thank to those people who has helped to develop the application,

[1] Graiman, B, Allison, B. Z, & Pfurtscheller, G. Brain-Computer Interfaces: Revolutio‐

[2] Galán, F, Nuttin, M, Lew, E, Ferrez, P. W, Vanacker, G, Philips, J, et al. A brain-actu‐ ated wheelchair: asynchronous and non-invasive Brain-computer interfaces for con‐ tinuous control of robots. Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology. (2008). Sep; , 119(9), 2159-69.

[3] Guger, C, & Edlinger, G. How many people can control a brain-computer interface.

[4] Sirvent, J. L, Azorín, J. M, Iáñez, E, Úbeda, A, & Fernández, E. Interfaz Cerebral no Invasiva Basada en Potenciales Evocados para el Control de un Brazo Robot. Revista iberoamericana de automática e informática industrial. (2011). Apr; , 8(2), 103-11.

[5] Lin, T. A, & John, L. R. Quantifying Mental Relaxation with EEG for use in Computer Games. In: International Conference on Internet Computing. Las Vegas, NV, United

[6] Purwanto, D, Mardiyanto, R, & Arai, K. Electric wheelchair control with gaze direc‐ tion and eye blinking. Artificial Life and Robotics. (2009). Dec 15; , 14(3), 397-400.

[7] Bear, M. F, Connors, B. W, & Paradiso, M. A. Neuroscience: Exploring the Brain.

[8] Duchowski, A. T. Eye Tracking Methodology: Theory and Practice. Second edi. New

[9] Muthmainnah, N, Noor, M, & Ahmad, S. Simulation Analysis of Different Strength Levels of EOG Signals. In: International Conference on Computer and Communica‐

Third. Philadelphia: Lippincott Williams & Wikins; (2007).

tion Engineering. Kuala Lumpur, Malaysia, July 3- 5, (2012). , 3-5.

nizing Human-Computer Interaction. Springer-V. New York: (2011).

especially to Eneko Lopetegui, because his advices and knowledge.

María Viqueira, Begoña García Zapirain and Amaia Mendez Zorrilla

Journal of Neuroscience letters. (2010). , 462, 94-8.

States, June 26- 29: (2006).

York: Springer; (2007).

Deustotech-LIFE, Universidad de Deusto, Bilbao, Spain

**Chapter 7**

**Novel Imaging Techniques in Gastrointestinal**

**Endoscopy in the Upper Gastrointestinal Tract**

The advent of high definition endoscopy has transformed the management of pre-malignant and early malignant diseases of the esophagus and upper gastrointestinal tract. The ability to view the mucosa in detail whereby the cellular architecture can be viewed has enabled the endoscopist to make in-vivo histopathological diagnoses, which in turn will direct the management of the pathology instantly. In this chapter, we describe the various techniques available from high definition white light endoscopy, through chromoendoscopy and confo‐ cal endomicroscopy. We describe the characteristics and staging of lesions of the esophagus including Barrett's esophagus (BE) and associated esophageal adenocarcinoma. Further‐ more, we describe how endoscopy can be used to define Barrett's and squamous dysplasia. Finally, we describe the classification and staging of early cancers of the esophagus and ex‐ plore the role of endoscopic ultrasound. We also examine the role of emerging radiological techniques such as virtual colonography that act as adjuncts to current practice and will no doubt help to focus the expertise of skilled endoscopists towards interventional endoscopy

Accurate diagnosis and staging of benign and malignant lesions of the esophagus requires an in-depth understanding of current endoscopic techniques and the latest technology. The endoscopic optical technology has evolved rapidly in the last decade such that the resolu‐ tion of the 'CCD" chip is up to 1.4 million pixels. The images are further enhanced by optical filters and post image processing technology allowing detailed views of the mucosal archi‐ tecture. This in turn allows improved accuracy of diagnosis. We explore the roles of high definition white light endoscopy, chromoendoscopy, confocal endomicroscopy and EUS in

and reproduction in any medium, provided the original work is properly cited.

© 2013 Haidry and Lovat; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution,

Rehan Haidry and Laurence Lovat

rather than routine diagnostic procedures.

the diagnosis and staging of esophageal neoplasia.

http://dx.doi.org/10.5772/53807

**1. Introduction**

Additional information is available at the end of the chapter

## **Novel Imaging Techniques in Gastrointestinal Endoscopy in the Upper Gastrointestinal Tract**

Rehan Haidry and Laurence Lovat

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/53807

#### **1. Introduction**

The advent of high definition endoscopy has transformed the management of pre-malignant and early malignant diseases of the esophagus and upper gastrointestinal tract. The ability to view the mucosa in detail whereby the cellular architecture can be viewed has enabled the endoscopist to make in-vivo histopathological diagnoses, which in turn will direct the management of the pathology instantly. In this chapter, we describe the various techniques available from high definition white light endoscopy, through chromoendoscopy and confo‐ cal endomicroscopy. We describe the characteristics and staging of lesions of the esophagus including Barrett's esophagus (BE) and associated esophageal adenocarcinoma. Further‐ more, we describe how endoscopy can be used to define Barrett's and squamous dysplasia. Finally, we describe the classification and staging of early cancers of the esophagus and ex‐ plore the role of endoscopic ultrasound. We also examine the role of emerging radiological techniques such as virtual colonography that act as adjuncts to current practice and will no doubt help to focus the expertise of skilled endoscopists towards interventional endoscopy rather than routine diagnostic procedures.

Accurate diagnosis and staging of benign and malignant lesions of the esophagus requires an in-depth understanding of current endoscopic techniques and the latest technology. The endoscopic optical technology has evolved rapidly in the last decade such that the resolu‐ tion of the 'CCD" chip is up to 1.4 million pixels. The images are further enhanced by optical filters and post image processing technology allowing detailed views of the mucosal archi‐ tecture. This in turn allows improved accuracy of diagnosis. We explore the roles of high definition white light endoscopy, chromoendoscopy, confocal endomicroscopy and EUS in the diagnosis and staging of esophageal neoplasia.

© 2013 Haidry and Lovat; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2013 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

#### **2. White Light Endoscopy (WLE)**

This process has several limitations. White light endoscopy is not sensitive enough to detect neoplasia in pre-cancerous conditions in the upper GI tract. For example in Barrett's esopha‐ gus, the standard approach is to take one biopsy in every quadrant of the Barrett's segment every 1-2 cm and send for histopathological review [1]. If biopsies are taken every 2 cm, the average number per procedure is 12 and if taken every 1cm, this number will double. Even with an efficient endoscopy setup, it takes around 30 seconds per biopsy so the procedure takes up to 30 minutes to perform. It is also very time consuming for the pathologist, need‐ ing up to 30 minutes to evaluate a set of biopsies from a single endoscopy. Dysplasia and early BE neoplasia result in subtle changes that may not often be visible with WLE examina‐ tion. In addition, random biopsies have significant sampling error since intestinal metapla‐ sia and dysplasia have a patchy distribution and only a small fraction of the BE segment is sampled in this way. Even the most rigorous biopsy protocols including those using jumbo biopsy forceps survey less than 1% of the esophageal mucosa and still miss up to one third of cases with high-grade dysplasia (HGD) or early cancer [2-5].

esophagus and 12 control patients. Methylene blue stained specialized columnar epithelium in 18 of the 26 patients, including those with intramucosal carcinoma (1), high-grade dyspla‐ sia (1), and indefinite/low-grade dysplasia (6). The overall sensitivity of methylene blue staining for the biopsy finding of specialized intestinal metaplasia was 95%. The same group then went on to a prospective, sequence randomized, trial of MDMB versus standard sur‐ veillance endoscopy with 2cm quadrantic biopsy [11]. 41 patients were studied with each procedure performed by separate endoscopists within an interval of 3 to 4 weeks. The aver‐ age number of biopsies was significantly lower with MBDB than 2cm quadrantic biopsy but the MB staining added a mean of 7 minutes (range 2 to 12 minutes) to the endoscopy proce‐ dure. Dysplasia or cancer was diagnosed in significantly more biopsy specimens (12% [12,13] vs. 6%, p = 0.004) and patients (44% vs. 28%, p = 0.03) by MBDB than by random bi‐

Novel Imaging Techniques in Gastrointestinal Endoscopy in the Upper Gastrointestinal Tract

http://dx.doi.org/10.5772/53807

139

**Figure 1.** Example of diffuse staining. Esophagus seen before and after staining with diffuse, uniform methylene blue

The problems with MB in BE is that dysplastic areas do not stain. Furthermore even areas which do not harbor IM do not absorb the dye. This makes it difficult for the endoscopist to decide on which areas to target the biopsies during the procedure. There are also some is‐ sues with the uniformity of the dye. It has been examined in both long and short segment BE [12,13,15]. Two patterns of staining have been documented - diffuse and focal. Canto *et al.* [15] found that most patients with long segment BE exhibited diffuse staining, whereas Wo *et al.* [16] observed focal staining in their cohort of patients with long segment BE. Similar results have been found when examining short segment BE by Sharma *et al.* [17] who found that the majority of their patients with short segment BE stained diffusely. In contrast, in 30 patients with short segment BE assessed by Kiesslich's group [18], only 80% demonstrated

A recent meta-analysis assessing the diagnostic yield of MB in detecting intestinal and dys‐ plasia in BE looked at 9 published studies that included 450 patients. Despite controlling for

opsy technique.

staining [14].

staining in a focal pattern.

#### **3. Chromoendoscopy**

The use of chromoendoscopy in the GI tract was first described in 1977 [6], and involves the topical application of stains or pigments to improve visualization of the mucosa during en‐ doscopy. The basics of performing chromoendoscopy require only a small number of items: staining agents, spray catheters, water rinses, and mucolytic agents. There are three main types of stains that are used:

There are two essential principles in chromoendoscopy: mucus removal and dye applica‐ tion. The former is achieved by using water, or occasionally some centers have advocated the use of a mucolytic agent; N-Acetylcysteine [7-9]. This can be achieved by flushing the agent through the working channel, using a spray catheter or even administering it as an oral solution before the endoscopic procedure. Once the mucus is cleared, the dye can then be applied.

#### **3.1. Methylene Blue (MB) chromoendoscopy**

MB, an absorptive dye, is probably the most investigated stain for evaluation of BE. MB is applied topically at a concentration of 0.5-1.0% and is absorbed by goblet cells present in metaplastic Barrett's epithelium. Much of the early work on MB has been performed by Canto's group [10]. The first series published in 1996 assessed 14 patients with Barrett's esophagus and 12 control patients. Methylene blue stained specialized columnar epithelium in 18 of the 26 patients, including those with intramucosal carcinoma (1), high-grade dyspla‐ sia (1), and indefinite/low-grade dysplasia (6). The overall sensitivity of methylene blue staining for the biopsy finding of specialized intestinal metaplasia was 95%. The same group then went on to a prospective, sequence randomized, trial of MDMB versus standard sur‐ veillance endoscopy with 2cm quadrantic biopsy [11]. 41 patients were studied with each procedure performed by separate endoscopists within an interval of 3 to 4 weeks. The aver‐ age number of biopsies was significantly lower with MBDB than 2cm quadrantic biopsy but the MB staining added a mean of 7 minutes (range 2 to 12 minutes) to the endoscopy proce‐ dure. Dysplasia or cancer was diagnosed in significantly more biopsy specimens (12% [12,13] vs. 6%, p = 0.004) and patients (44% vs. 28%, p = 0.03) by MBDB than by random bi‐ opsy technique.

**2. White Light Endoscopy (WLE)**

138 Medical Imaging in Clinical Practice

**3. Chromoendoscopy**

types of stains that are used:

be applied.

of cases with high-grade dysplasia (HGD) or early cancer [2-5].

**i.** Absorptive stains (methylene blue, Lugol's solution)

**ii.** Contrast stains (indigo carmine, acetic acid)

**iii.** Reactive stains such as congo red or phenol

**3.1. Methylene Blue (MB) chromoendoscopy**

This process has several limitations. White light endoscopy is not sensitive enough to detect neoplasia in pre-cancerous conditions in the upper GI tract. For example in Barrett's esopha‐ gus, the standard approach is to take one biopsy in every quadrant of the Barrett's segment every 1-2 cm and send for histopathological review [1]. If biopsies are taken every 2 cm, the average number per procedure is 12 and if taken every 1cm, this number will double. Even with an efficient endoscopy setup, it takes around 30 seconds per biopsy so the procedure takes up to 30 minutes to perform. It is also very time consuming for the pathologist, need‐ ing up to 30 minutes to evaluate a set of biopsies from a single endoscopy. Dysplasia and early BE neoplasia result in subtle changes that may not often be visible with WLE examina‐ tion. In addition, random biopsies have significant sampling error since intestinal metapla‐ sia and dysplasia have a patchy distribution and only a small fraction of the BE segment is sampled in this way. Even the most rigorous biopsy protocols including those using jumbo biopsy forceps survey less than 1% of the esophageal mucosa and still miss up to one third

The use of chromoendoscopy in the GI tract was first described in 1977 [6], and involves the topical application of stains or pigments to improve visualization of the mucosa during en‐ doscopy. The basics of performing chromoendoscopy require only a small number of items: staining agents, spray catheters, water rinses, and mucolytic agents. There are three main

There are two essential principles in chromoendoscopy: mucus removal and dye applica‐ tion. The former is achieved by using water, or occasionally some centers have advocated the use of a mucolytic agent; N-Acetylcysteine [7-9]. This can be achieved by flushing the agent through the working channel, using a spray catheter or even administering it as an oral solution before the endoscopic procedure. Once the mucus is cleared, the dye can then

MB, an absorptive dye, is probably the most investigated stain for evaluation of BE. MB is applied topically at a concentration of 0.5-1.0% and is absorbed by goblet cells present in metaplastic Barrett's epithelium. Much of the early work on MB has been performed by Canto's group [10]. The first series published in 1996 assessed 14 patients with Barrett's

**Figure 1.** Example of diffuse staining. Esophagus seen before and after staining with diffuse, uniform methylene blue staining [14].

The problems with MB in BE is that dysplastic areas do not stain. Furthermore even areas which do not harbor IM do not absorb the dye. This makes it difficult for the endoscopist to decide on which areas to target the biopsies during the procedure. There are also some is‐ sues with the uniformity of the dye. It has been examined in both long and short segment BE [12,13,15]. Two patterns of staining have been documented - diffuse and focal. Canto *et al.* [15] found that most patients with long segment BE exhibited diffuse staining, whereas Wo *et al.* [16] observed focal staining in their cohort of patients with long segment BE. Similar results have been found when examining short segment BE by Sharma *et al.* [17] who found that the majority of their patients with short segment BE stained diffusely. In contrast, in 30 patients with short segment BE assessed by Kiesslich's group [18], only 80% demonstrated staining in a focal pattern.