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Comparative Analysis of Proposed Artificial Neural Network (ANN) Algorithm With Other Techniques
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Author(s): Deepak Chatha (Department of Computer Science and Engineering, Panipat Institute of Engineering and Technology, Samalkha, India), Alankrita Aggarwal (Department of Computer Science and Engineering, Panipat Institute of Engineering and Technology, Samalkha, India)and Rajender Kumar (Department of Computer Science and Engineering, Panipat Institute of Engineering and Technology, Samalkha, India)
Copyright: 2020
Volume: 12
Issue: 1
Pages: 7
Source title:
International Journal of Security and Privacy in Pervasive Computing (IJSPPC)
Editor(s)-in-Chief: Tao Gao (Zionlion Group Ltd. Shanghai, China)
DOI: 10.4018/IJSPPC.2020010103
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Abstract
The mortality rate among women is increasing progressively due to cancer. Generally, women around 45 years old are vulnerable from this disease. Early detection is hope for patients to survive otherwise it may reach to unrecoverable stage. Currently, there are numerous techniques available for diagnosis of such a disease out of which mammography is the most trustworthy method for detecting early cancer stage. The analysis of these mammogram images are difficult to analyze due to low contrast and nonuniform background. The mammogram images are scanned and digitized for processing that further reduces the contrast between Region of Interest and background. Presence of noise, glands and muscles leads to background contrast variations. Boundaries of suspected tumor area are fuzzy & improper. Aim of paper is to develop robust edge detection technique which works optimally on mammogram images to segment tumor area. Output results of proposed technique on different mammogram images of MIAS database are presented and compared with existing techniques in terms of both Qualitative & Quantitative parameters.
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