Relation U-Net
Journal:
arXiv
Published Date:
Jan 15, 2025
Abstract
Towards clinical interpretations, this paper presents a new
''output-with-confidence'' segmentation neural network with multiple input
images and multiple output segmentation maps and their pairwise relations. A
confidence score of the test image without ground-truth can be estimated from
the difference among the estimated relation maps. We evaluate the method based
on the widely used vanilla U-Net for segmentation and our new model is named
Relation U-Net which can output segmentation maps of the input images as well
as an estimated confidence score of the test image without ground-truth.
Experimental results on four public datasets show that Relation U-Net can not
only provide better accuracy than vanilla U-Net but also estimate a confidence
score which is linearly correlated to the segmentation accuracy on test images.
