Abstract
Cancer is a group of diseases involving abnormal cell growth with the potential to invade or spread to other parts of the body. Breast cancer is the most prevalent cancer among women worldwide and histopathological evaluation of lymph node and whole-slide images (WSIs) play an important role in detection and curing. In this paper, we propose a method to automatically predict pN-stage for whole slide image by leveraging multi-scale features and path aggregation. We used cross-validation on Convolutional Neural Networks (CNN) architecture with fast ai densenet [1] (AUC>0.975) for slide level detection of tumor cells.
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