A Classification Scheme for Lymphocyte Segmentation in H&E Stained Histology Images

• Published in: Recognizing Patterns in Signals, Speech, Images and Videos pp. 235 - 243
• Main Authors: Kuse, Manohar, Sharma, Tanuj, Gupta, Sudhir
• Format: Book Chapter
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2010
• Series: Lecture Notes in Computer Science
• Subjects: Classification; Contour Overlap Resolution; Lymphocytes
• ISBN: 9783642177101; 3642177107
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-642-17711-8_24

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.