MRI based Breast Cancer Segmentation and Classification using Machine Learning Techniques
Nagaraja Rao P.P.1, D. Venkatasekhar2, P. Venkatramana3, Chowdavarapu Usha Rani4

1Nagaraja Rao P.P.*, Department of Electronics & Communication Engineering, Annamalai University, Annamalainagar, India.
2Dr. D. Venkatasekhar, Department of Information Technology, Annamalai University, Annamalainagar, India.
3Dr. P. Venkatramana, Department of Electronics & Communication, Sree Vidyanikethan Engineering College, Tirupati, India.
4Chowdavarapu Usha Rani, Department of Computer Science & Engineering, Annamachaya Institute of Technology & Sciences, Tirupati, India. 

Manuscript received on November 13, 2019. | Revised Manuscript received on 23 November, 2019. | Manuscript published on December 10, 2019. | PP: 727-731 | Volume-9 Issue-2, December 2019. | Retrieval Number: B6827129219/2019©BEIESP | DOI: 10.35940/ijitee.B6827.129219
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Abstract: Presently, the death rate of breast cancer among women is in dangerous proposition in both developing and developed countries. This threat is addressed by the effective detection of breast cancer in earlier stages. Henceforth, the early detection of breast cancer enhances the probability of cure and survival rate. So, it is vital to develop an automated system for detecting the breast cancer in earlier stages. Magnetic Resonance Imaging (MRI) is the regularly utilized diagnosis tool for detecting and classifying the normalities and abnormalities of breast. This paper analysis the previous research carried-out in breast cancer detection and also explores the issues faced by the researchers in existing works. In addition, this paper assists the researchers for attaining better solution to the current problems faced in breast cancer detection.
Keywords: Breast Cancer Detection, Machine Learning technique, Magnetic Resonance Imaging, Mammogram Segmentation and Classification.
Scope of the Article: Classification