Features Fusion for Dual-View Mammography Mass Detection

arXiv:2404.16718v1 Announce Type: cross
Abstract: Detection of malignant lesions on mammography images is extremely important for early breast cancer diagnosis. In clinical practice, images are acquired from two different angles, and radiologists can fully utilize information from both views, simultaneously locating the same lesion. However, for automatic detection approaches such information fusion remains a challenge. In this paper, we propose a new model called MAMM-Net, which allows the processing of both mammography views simultaneously by sharing information not only on …

abstract acquired arxiv cancer cancer diagnosis clinical cs.ai cs.cv cs.lg detection diagnosis eess.iv features fusion however images information mammography practice type view