Solving mammography problems of breast cancer detection using artificial neural networks and image processing techniques

Moh   d Rasoul A   Al Hadidi; Mohammed Y  Al Gawagzeh and    Bayan A  Alsaaidah

doi:10.17485/ijst/2012/v5i4.13

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Solving mammography problems of breast cancer detection using artificial neural networks and image processing techniques

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Indian Journal of Science and Technology

DOI: 10.17485/ijst/2012/v5i4.13

Year: 2012, Volume: 5, Issue: 4, Pages: 1-9

Original Article

Solving mammography problems of breast cancer detection using artificial neural networks and image processing techniques

^1*Moh’d Rasoul A . Al-Hadidi,^² Mohammed Y. Al-Gawagzeh and ^³ Bayan A. Alsaaidah

Computer Engineering Department, [email protected]*
[email protected]
[email protected]
*Author For Correspondence
^1*Moh’d Rasoul A . Al-Hadidi
Computer Engineering Department,
Email: [email protected]

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

In this paper, we propose a complementary technique of breast cancer diagnosis that covers five stages of breast cancer detection based on mammography, which solves many of the problems found otherwise. We also show a very large area w h e r e many methods and techniques can be successfully merged in order to obtain a useful result for human use. These include scaling of the image, removing small objects, smoothing, extracting features, ROI extraction and many image processing techniques. Besides, neural networks are used here to train the system to detect cancer according to the dataset. This combination of multiple techniques can solve problems of the breast cancer detection with a high degree of accuracy. Examples and comparisons are given to illustrate and prove this method.
Keywords: Breast cancer, Benign, Mammography, Image processing, Neural networks