A comprehensive survey on deep active learning in medical image analysis

arXiv:2310.14230v3 Announce Type: replace
Abstract: Deep learning has achieved widespread success in medical image analysis, leading to an increasing demand for large-scale expert-annotated medical image datasets. Yet, the high cost of annotating medical images severely hampers the development of deep learning in this field. To reduce annotation costs, active learning aims to select the most informative samples for annotation and train high-performance models with as few labeled samples as possible. In this survey, we review the core methods of active …

abstract active learning analysis annotation arxiv cost costs cs.cv datasets deep learning demand development expert image image datasets images medical reduce scale success survey type