Title: Detection of masses in mammographic breast cancer images using modified histogram based adaptive thresholding (MHAT) method

Authors: Bhagwati Charan Patel; G.R. Sinha; Dilip Soni

Addresses: Department of IT, Faculty of Engineering and Technology of SSTC, Bhilai, India ' Department of ETC, Faculty of Engineering and Technology of SSTC, Bhilai, India ' Vision: Research and Diagnostic Center, Bhilai, India

Abstract: Breast cancer is the leading type of cancer diagnosed in women nowadays and for breast screening, mammography is preferred to detect and diagnose the cancer by detecting the masses with the help of Computer-aided Diagnosis (CAD) system. It helps to assist radiologists in getting accurate diagnosis. An approach is proposed to effectively detect the masses in mammographic breast cancer images by using Modified Histogram based adaptive thresholding (MHAT) method. The algorithm has been tested over with 100 mammographic images and the experimental results show that the detection method has a sensitivity of 98.3% at 0.78 false positives with accuracy of 99% per image. We evaluated the performance of our MHAT algorithm by comparing with respect to the ground-truth boundary drawn by an expert radiologist. The results are clinically relevant, according to the radiologists who evaluated the results.

Keywords: adaptive thresholding; breast cancer; computer aided detection; mammography; mass; segmentation; screening.

DOI: 10.1504/IJBET.2019.097302

International Journal of Biomedical Engineering and Technology, 2019 Vol.29 No.2, pp.134 - 154

Received: 25 May 2016
Accepted: 04 Oct 2016
Published online: 14 Jan 2019 *

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