Medical Diagnostic Systems for Breast Cancer
Manik Rakhra1, Mandeep Kaur2, Jimmy Singla3
1Manik Rakhra*, Assistant Professor, School of Computer Science and Engineering, Lovely Professional University, Punjab.
2Mandeep Kaur, Pursuing M. Tech in School of Computer Science and Engineering, Lovely Professional University, Punjab.
3Jimmy Singla, Associate Professor, School of Computer Science and Engineering at Lovely Professional University, Punjab.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 30, 2020. | Manuscript published on April 10, 2020. | PP: 945-949 | Volume-9 Issue-6, April 2020. | Retrieval Number: F3891049620/2020©BEIESP | DOI: 10.35940/ijitee.F3891.049620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Breast Cancer is one of the diseases where females have the highest mortality rate. Early detection is the way to diminishing the rate and helps increase the lifespan of suffering patients. Mammography is the method of using low energy X-rays for examination and screening the human breast. A team of radiologists required for the analysis of mammograms, but even experienced experts can misjudge in their evaluation.so Computer-Aided Detection (CAD) systems are having more pervasive for the purpose. There are various abnormalities, including micro-calcifications, are identified from mammograms. This study takes a look at all techniques that are helpful in detecting calcification. Several works of literature have been reviewed to explore and learn the outstanding way in different cases and situations for the sensing of classification in cancer of breast.
Keywords: X-ray, Breast Cancer, CAD, Mammogram
Scope of the Article: Adaptive Systems