EMT-NET: Efficient multitask network for computer-aided diagnosis of breast cancer. (arXiv:2201.04795v1 [eess.IV])

Deep learning-based computer-aided diagnosis has achieved unprecedented
performance in breast cancer detection. However, most approaches are
computationally intensive, which impedes their broader dissemination in
real-world applications. In this work, we propose an efficient and
light-weighted multitask learning architecture to classify and segment breast
tumors simultaneously. We incorporate a segmentation task into a tumor
classification network, which makes the backbone network learn representations
focused on tumor regions. Moreover, we propose a new numerically stable loss
function that easily controls the balance …

arxiv cancer network