Learning with Less Labels in Digital Pathology via Scribble Supervision from Natural Images. (arXiv:2201.02627v2 [eess.IV] UPDATED)

Web: http://arxiv.org/abs/2201.02627

A critical challenge of training deep learning models in the Digital
Pathology (DP) domain is the high annotation cost by medical experts. One way
to tackle this issue is via transfer learning from the natural image domain
(NI), where the annotation cost is considerably cheaper. Cross-domain transfer
learning from NI to DP is shown to be successful via class labels. One
potential weakness of relying on class labels is the lack of spatial
information, which can be obtained from spatial …

arxiv digital images learning natural