论文《A Survey on Deep Learning in Medical Image Analysis
》长达34页的基于深度学习的医学图像分析综述,全面总结了近年来深度学习在分类、检测、分割和配准等医学图像上的相关工作。
摘要:
Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks and provide concise overviews of studies per application area. Open challenges and directions for future research are discussed.
原文链接:
https://arxiv.org/abs/1702.05747