A classification scheme for lymphocyte segmentation in H&E stained histology images

Authors:
Manohar Kuse;Tanuj Sharma;Sudhir Gupta
Affiliations:
The LNM Institute of Information Technology, Jaipur, India;The LNM Institute of Information Technology, Jaipur, India;The LNM Institute of Information Technology, Jaipur, India
Venue:
ICPR'10 Proceedings of the 20th International conference on Recognizing patterns in signals, speech, images, and videos
Year:
2010

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Abstract

A technique for automating the detection of lymphocytes in histopathological images is presented. The proposed system takes Hematoxylin and Eosin (H&E) stained digital color images as input to identify lymphocytes. The process involves segmentation of cells from extracellular matrix, feature extraction, classification and overlap resolution. Extracellular matrix segmentation is a two step process carried out on the HSV-equivalent of the image, using mean shift based clustering for color approximation followed by thresholding in the HSV space. Texture features extracted from the cells are used to train a SVM classifier that is used to classify lymphocytes and non-lymphocytes. A contour based overlap resolution technique is used to resolve overlapping lymphocytes.