Shwetha S.V.

Work place: Sri Dharmasthala Manjunatheshwara Institute of Technology, Ujire – 574 240, Visvesvaraya Technological University, Belagavi, Karnataka, India



Research Interests: Medical Image Computing, Image Processing, Image Manipulation, Image Compression, Medical Informatics


Ms. Shwetha S.V., the research scholar, pursuing Ph.D. in the stream of Image processing under Visvesvaraya Technological University, Belagavi. She had completed her M.Tech. and B.E. in the year 2013 and 2008 respectively. She had 12 years of teaching experience at SDMIT Ujire. She had published her four research article in SCOPUS indexed International journal and one in International Conference. Her area of interest is medical image processing

Author Articles
An Automatic Recognition, Identification and Classification of Mitotic Cells for the Diagnosis of Breast Cancer Stages

By Shwetha S.V. Dharmanna L

DOI:, Pub. Date: 8 Dec. 2021

The identification of breast cancer stages plays a vital role for understanding the aggressiveness of cancer disease and the patient survival as an outcome. The main parameter of breast cancer staging is counting the mitotic cells in biopsy samples of breast cancer tissues. In the present scenario the manually counting of the mitotic cells in histopathology image slides of the tissue examined by the expert under clinical microscope is 10X, 20X ,40X ,100X,400X magnification of the sample. The manual process is laborious, inaccurate, erroneous and tedious, hence the traditional method demands the computerized approach to recognize and identify the cancer stages for the expert to come up with robust decision. In this work we proposed a novel approach for automatic recognition and identification through computer aided diagnosis systems (CAD). In this CAD proposed model the work is divided into five stages. In the first stage histopathological image are preprocessed to enhance the contrast of the mitotic cells and non mitotic cells using image adjustment technique. In second stage the foreground and background is segmented using Otsu segmentation algorithm. In the third stage the Bit plane slicing is applied to separate the mitotic and non mitotic cells. In the fourth stage the number of mitotic cells is counted in the samples. In the fifth stage of the work, based on the number of mitotic cells the cancer stages are determined. In this work, ICPR 2012 database images are adopted for the experimentation. The diagnosis of the stage of the cancer will help the oncologist to take proper decision and also reduces the burden of the work.

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