Label uncertainty-guided multi-stream model for disease screening. (arXiv:2201.12089v1 [cs.CV])

Web: http://arxiv.org/abs/2201.12089

The annotation of disease severity for medical image datasets often relies on
collaborative decisions from multiple human graders. The intra-observer
variability derived from individual differences always persists in this
process, yet the influence is often underestimated. In this paper, we cast the
intra-observer variability as an uncertainty problem and incorporate the label
uncertainty information as guidance into the disease screening model to improve
the final decision. The main idea is dividing the images into simple and hard
cases by uncertainty …

arxiv cv disease model uncertainty