Breast Cancer Detection

Document Type

News Article

Abstract

Female breast cancer has become the most often diagnosed type of cancer in the world and has become a major health concern across rural and urban areas in India nowadays. Asian women are more likely to have dense breasts than other women in the world. Dense breast tissue, on the other hand, can make it more difficult to detect breast cancer and is linked to an increased risk of breast cancer. Digital Mammography is a very useful technique for screening and has long been acknowledged as the most reliable method for detecting breast cancer at an early stage, but its accuracy is limited by radiologists' clinical experience.

To solve this problem a novel fully automated deep learning-based breast cancer computer-aided diagnosis system (CAD) enabled with a graphical user interface is proposed. Quantitative research will be conducted focusing on Digital Mammogram pre-processing, image segmentation to detect regions of interest, and classification of these images based on the Breast Imaging-Reporting and Data System (BI-RADS) using deep learning models. The CAD system hence designed based on the retrospective data collected will be validated prospectively in the hospital setup.

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Publication Date

Winter 11-1-2022

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