Self-semantic contour adaptation for cross modality brain tumor segmentation. (arXiv:2201.05022v1 [cs.CV])

Unsupervised domain adaptation (UDA) between two significantly disparate
domains to learn high-level semantic alignment is a crucial yet challenging
task.~To this end, in this work, we propose exploiting low-level edge
information to facilitate the adaptation as a precursor task, which has a small
cross-domain gap, compared with semantic segmentation.~The precise contour then
provides spatial information to guide the semantic adaptation. More
specifically, we propose a multi-task framework to learn a contouring
adaptation network along with a semantic segmentation adaptation network, …

arxiv brain cv segmentation semantic