(Fig \[LSF\]-d). It is to be noted that a similar computation shown in Eqn. \[Inverting\] and \[Intensity\] can be done with ’G’ instead of ’R’ in the RGB pixel values as well to get a similar result. The next step in the input video development is to use the distance regularized level-set evolution (DRLSE) [@li2010distance] image segmentation for all the images of the same video (Fig \[LSF\]-e) to segment the valve’s leaflets in each frame. The initial level-set contour has also been depicted in Fig. \[LSF\]-(e) along with the final result (Fig. \[LSF\]-(f)). Then, A polynomial interpolation is used to interpolate the data set into a fixed number of points for all the frames. For the mitral orifice data, as shown in Fig. \[valve\] a cubic-spline interpolation coupled with weighted moving average (span=20) for data smoothing was employed.

The mitral and aortic orifice data are oriented using angular orientation value of the SA basal from the LV optimization process explained in section \[Scaling\]. In addition, The scaling of the mitral data as seen in the 3 LA Apical views (Fig \[valve\_ident\]-a to Fig \[valve\_ident\]-c) and orifice as observed in the SA Basal section (Fig \[valve\_ident\]-d) is performed as follows. First 