Artificial Intelligence for early Detection of Breast Cancer and Classification of Mammographic Masses
Sujata Patil1, Shweta Madiwalar2, V M Aparanji3
1Dr.Sujata N Patil, Associate Professor at KLE Dr.M.S.Sheshgiri College and Engg, Belagavi, India.
2Prof. Shweta M Madiwalar, Assistant Professor at KLE Dr.M.S.Sheshgiri College and Engg ,Belagavi, India.
3Dr. V M Aparanji, Assistant Professor at Siddaganga Institute of Technology, Tumkur, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 4315-4320 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9219038620/2020©BEIESP | DOI: 10.35940/ijrte.F9219.038620
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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: Every single year thousands of women endure painful and invasive surgery to remove breast lesions. Most of the time the mammographic image analysis leads to false positive detection and the majority of this actions reveal the lesions to be benign. Refining present detection and diagnostic tool is a major priority of our work. MATLAB R2015a is been used to develop the algorithm, which aids in detection of breast cancer in its early stage. The algorithm comprises of image processing and applying artificial intelligence where in the system is trained with a set of images so that when the input or the test image is given, the algorithm performs the image processing techniques and then applies the Probabilistic Neural Network (PNN) technique for detection of cancer. The system performance is also been calculated in order to estimate its reliability.
Keywords: Neural Network, Artificial Intelligence, Benign, Malignant, Probabilistic Neural Network (PNN),
Scope of the Article: Classification.