Automatic classification of coating epithelial tissue

Abstract

Histology images may be used in E-Learning systems to teach how morphological features and function of each organ contribute to its identification. Automatic classification of coating epithelial cells is an open problem in image processing. This problem has been addressed using morphological gradient, region-based and, shape-based method, among others. In this paper, coating epithelial cells are recognised and classified into: Flat, Cubic and Cylindrical. Epithelial cells are classified based on sphericity and projection. Information about sphericity is used to classify cells into cubic and a measure based in projecting cell nucleus into light region is used to classify into flat and cylindrical. Experimental validations are conducted according to expert criteria, along with manually annotated images, as a ground-truth. Experimental results revealed that the proposed approach recognised coating epithelial cells and classified tissues in a similar way to how experts have performed these classifications.