Breast cancer histology classification using Deep Residual Networks

1 code implementation • Engineering in Medicine and Biology Society (EMBC), 2018 40th Annual International Conference of the IEEE 2018 • Kamalakkannan Ravi, Sakthivel Selvaraj, JM Poorneshwaran, Keerthi Ram, Mohanasankar Sivaprakasam

In this work, in order to improve the computer aided diagnosis systems’ performance on histopathological image analysis, we have proposed an approach with image pre-processing followed by a deep learning method to classify the breast cancer histology images into four classes; (i) normal tissue, (ii) benign lesion, (iii) in-situ carcinoma, and (iv) invasive carcinoma.

Breast Cancer Histology Image Classification Classification +1