Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reference-guided Pseudo-Label Generation for Medical Semantic
  Segmentation   Producing densely annotated data is a difficult and tedious task for medical
imaging applications. To address this problem, we propose a novel approach to
generate supervision for semi-supervised semantic segmentation. We argue that
visually similar regions between labeled and unlabeled images likely contain
the same semantics and therefore should share their label. Following this
thought, we use a small number of labeled images as reference material and
match pixels in an unlabeled image to the semantics of the best fitting pixel
in a reference set. This way, we avoid pitfalls such as confirmation bias,
common in purely prediction-based pseudo-labeling. Since our method does not
require any architectural changes or accompanying networks, one can easily
insert it into existing frameworks. We achieve the same performance as a
standard fully supervised model on X-ray anatomy segmentation, albeit 95% fewer
labeled images. Aside from an in-depth analysis of different aspects of our
proposed method, we further demonstrate the effectiveness of our
reference-guided learning paradigm by comparing our approach against existing
methods for retinal fluid segmentation with competitive performance as we
improve upon recent work by up to 15% mean IoU.

9
The categories of this paper are: nlin
14
The categories of this paper are: math-ph
35
The categories of this paper are: mtrl-th
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
32
The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc
0
The categories of this paper are: hep-ph
21
The categories of this paper are: adap-org