Image Classification for Breast Cancer Using a Modified Convolution Neural Network Architecture

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Priya Porwal
Ajay Shankar Singh
Thirunavukkarasu K.


The most common type of cancer that results in death is breast cancer. In the world, millions of people struggle with this disease. Breast cancer can affect men and women but women are more affected. For awareness, it is necessary to understand the sign and symptoms of breast cancer. The most common sign is an abnormal lump in the breast. But there may be many reasons of develop abnormal lumps. Computer-Aided Diagnosis (CAD) is extensively used in pathological image analysis to help pathologists enhance diagnosis efficiency, accuracy, and consistency. Recent studies have looked into deep learning methodologies to improve the effectiveness of pathological CAD.

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Porwal, P. ., Singh, A. S. ., & K., T. . (2023). Image Classification for Breast Cancer Using a Modified Convolution Neural Network Architecture. International Journal on Recent and Innovation Trends in Computing and Communication, 11(9s), 615–622.


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