Neural Network Based Classification of Digital Mammograms using DCT Coefficients
| Author(s) | : | Assistant Prof T. Krishna Chaitanya, P. Chandra Sekhar Azad |
| Institution | : | Electronics and communication Engineering, Bapatla Engineering College |
| Published In | : | Vol. 4, Issue 8 — August 2017 |
| Page No. | : | 15-20 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
Breast cancer is very common among the World’s women population. Early detection of breast cancer canreduce the effect. Mammography based diagnosis is considered as the most effective to detect breast cancer. But,mammogram images often lead to misdiagnosis due to their low contrast nature. Recent studies show that mammographybased diagnosis fails to detect cancerous lumps in the breast in fifteen out of one hundred patients. In this paper, weproposed a neural network based breast cancer detection technique. In the proposed method mammogram images areenhanced and Region of Interest (ROI) extracted to locate the malignant lumps in the women’s breast. The DiscreteCosine Transform coefficients of ROI images are obtained, a simple multilayer feed forward neural network is used totrain with these coefficients and tested in order to classify the Digital Mammograms. The results are compared with theexisting method and the superiority of the proposed method in terms of various metrics is justified.
Assistant Prof T. Krishna Chaitanya, P. Chandra Sekhar Azad, “Neural Network Based Classification of Digital Mammograms using DCT Coefficients”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 8, pp. 15-20, August 2017.
