Histoloji Görüntülerinde Kanserli Desenlerin Yarı Güdümlü Öğrenme Yöntemiyle Tam Otomatik Sınıflandırılması

Abstract

The aim of this work is to perform automated texture classification of histology slide images in health and cancerous conditions using quasi-supervised statistical learning method. Tissue images were acquired from histological slides of human colon and were seperated into two groups in terms of normal and disease conditions. Texture feature vectors corresponding to tissue segments of each image were calculated using co-occurrence matrices. Different texture regions were determined by the quasi-supervised statistical learning method using texture features of normal and cancerous groups. ©2010 IEEE.