Review: A Detail Comparison with Analysis of Computer-Aided Breast Cancer Detection Techniques

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Saguna Ingle, Amarsinh Vidhate, Sangita Chaudhari

Abstract

Breast cancer is the deadliest cancer all over the world for women. A breast Cancer diagnosis at an early stage is important for women, to minimize the damage, discomfort and provide a potential cure. Mammography is the most reliable screening tool for the identification of any signs of malignancy or abnormality about the cyst. There are many invasive cancer diagnosis methods available but that all are painful and costly. Computer-Aided Diagnosis (CAD) are dynamic tools that can support radiologists to detect and classify mammographic abnormalities. In this digitalized era, CAD is the need of the medical field. In CAD for breast cancer detection allows the oncologist and the physicians a second opinion, and it saves their time and reduces the false positive probability in the breast cancer diagnosis process. Advanced classification techniques and enhanced image processing and segmentation are needed to enhance the performance of CAD.

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How to Cite
Saguna Ingle, Amarsinh Vidhate, Sangita Chaudhari. (2022). Review: A Detail Comparison with Analysis of Computer-Aided Breast Cancer Detection Techniques. Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(14), 5978–5995. https://doi.org/10.17762/turcomat.v12i14.12175
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