title: Image Segmentation with TensorFlow
body: <p>I am trying to see the feasibility of using TensorFlow to identify features in my image data. I have 50x50px grayscale images of nuclei that I would like to have segmented- the desired output would be either a 0 or 1 for each pixel.  0 for the background, 1 as the nucleus.</p>
  
  <p>Example input: <a href="http://i.stack.imgur.com/OvoWa.jpg" rel="nofollow">raw input data</a></p>
  
  <p>Example label (what the "label"/real answer would be): <a href="http://i.stack.imgur.com/CR2aL.jpg" rel="nofollow">output data (label)</a></p>
  
  <p>Is it even possible to use TensorFlow to perform this type of machine learning on my dataset?  I could potentially have thousands of images for the training set.   </p>
  
  <p>A lot of the examples have a label correspond to a single category, for example, a 10 number array [0,0,0,0,0,0,0,0,0,0,0] for the handwritten digit data set, but I haven't seen many examples that would output a larger array.  I would assume I the label would be a 50x50 array? </p>
  
  <p>Also, any ideas on the processing CPU time for this time of analysis?  </p>