title: Detection and Classification of Cancer from Microscopic Biopsy Images Using Clinically Significant and Biologically Interpretable Features.
abstract: A framework for automated detection and classification of cancer from microscopic biopsy images using clinically significant and biologically interpretable features is proposed and examined. The various stages involved in the proposed methodology include enhancement of microscopic images, segmentation of background cells, features extraction, and finally the classification. An appropriate and efficient method is employed in each of the design steps of the proposed framework after making a comparative analysis of commonly used method in each category. For highlighting the details of the tissue and structures, the contrast limited adaptive histogram equalization approach is used. For the segmentation of background cells, k-means segmentation algorithm is used because it performs better in comparison to other commonly used segmentation methods. In feature extraction phase, it is proposed to extract various biologically interpretable and clinically significant shapes as well as morphology based features from the segmented images. These include gray level texture features, color based features, color gray level texture features, Law's Texture Energy based features, Tamura's features, and wavelet features. Finally, the K-nearest neighborhood method is used for classification of images into normal and cancerous categories because it is performing better in comparison to other commonly used methods for this application. The performance of the proposed framework is evaluated using well-known parameters for four fundamental tissues (connective, epithelial, muscular, and nervous) of randomly selected 1000 microscopic biopsy images.
authors.affiliation: Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi 221005, India.
authors.forename: Rajesh
authors.initials: R
authors.lastname: Kumar
authors.affiliation: Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi 221005, India.
authors.forename: Rajeev
authors.identifier: 0000-0002-0165-1556
authors.initials: R
authors.lastname: Srivastava
authors.affiliation: Department of Computer Science and Engineering, Indian Institute of Technology (Banaras Hindu University), Varanasi 221005, India.
authors.forename: Subodh
authors.initials: S
authors.lastname: Srivastava