Classification of Histopathological Images Through Bag-of-Visual-Words and Gravitational Search Algorithm

Abstract

The automated quantification of different cell structures available in histopathological images is a challenging task due to the presence of complex background structures. Moreover, the tissues of different categories, namely epithelium tissue, connective tissue, muscular tissue, and nervous tissue have heterogeneous structure which limits the applicability of an algorithm to only a single class of tissue for the quantification analysis of histopathological images. Therefore, this paper introduces a novel method for categorization of histopathological images into the respective tissue category before quantification analysis. The proposed method uses SIFT method for feature extraction which are further processed by gravitational search algorithm to obtain optimal bag-of-visual-words. Moreover, support vector machine is trained on these bag-of-visual-words to classify the images into respective categories. The experimental results show that the proposed method outperforms the traditional K-means-based method for histopathological image classification.