title: Image segmentation based on edge pixel map
body: <p>I have trained a classifier in Python for classifying pixels in an image of cells as edge or non edge. I've used it successfully on a few image datasets but am running into problems with this particular dataset, which seems pretty ambiguous even to the human eye. I don't know of any existing automated technique that can segment it accurately. </p>
  
  <p>After prediction I obtain the following image: </p>
  
  <p><img src="https://i.stack.imgur.com/9JMva.jpg" alt="Prediction image"></p>
  
  <p>I am relatively new to image processing and am unsure with how to proceed with actually obtaining the final segmentations of the cells. I have briefly tried a few different techniques - namely Hough circular transform, level sets, skeletonization, contour finding - but none have really done the trick. Am I just not tuning the parameters correctly or is there a better technique out there? </p>
  
  <p>Here are the correct outlines, by the way, for reference. </p>
  
  <p><img src="https://i.stack.imgur.com/ijjnj.png" alt="Correct outlines"></p>
  
  <p>And the original image:</p>
  
  <p><img src="https://i.stack.imgur.com/urhGH.png" alt="enter image description here"></p>
  
  <p>And the continuous probability map: </p>
  
  <p><img src="https://i.imgur.com/reoh0pb.png" alt="Continuous probability map"></p>