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Color deconvolution method for breast tissue core biopsy images cell nuclei detection and analysis using multiresolution techniques

S. Issac Niwas, P. Palanisamy, Ewert Bengtsson

Abstract


Breast cancer is the second most common cause of cancer induced death in women in the world. Testing for detection of the cancer involves visual microscopic assessment of breast tissue samples such as core needle biopsies. Analysis on this sample by pathologist is crucial for breast cancer patient. In this paper, a color deconvolution method is used to detect nuclei of core needle biopsy images and then it is investigated after decomposition by means of the curvelet transform. The curvelet statistical features are used for breast
cancer diagnosis using the Naïve Bayes Classifier (NBC) system. The ability of properly trained Naïve Bayes Classifiers correctly classify and recognize patterns which is particularly suitable for use in an expert system assisting the diagnosis of cancer tissue samples.

Keywords


Breast tissue image, Color deconvolution, Curvelet transform, Texture analysis, Naïve bayes classifier

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