A support system for diagnosing pathological image using CNN

Abstract

In this paper, we propose a method to extract nuclear area in pathological images for diagnosis of endometrial endometrioid adenocarcinoma. Firstly, we divide on image into small areas called superpixels. Secondly, we classify the superpixels into two classes (nucleus or background). Finally, we specify seed points using previous results, and perform division by GrabCut. By the specification of the seeds from the result of GrabCut, we have made it possible to perform highly accurate extraction.