Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor
  Segmentation   Kidney tumor segmentation emerges as a new frontier of computer vision in
medical imaging. This is partly due to its challenging manual annotation and
great medical impact. Within the scope of the Kidney Tumor Segmentation
Challenge 2019, that is aiming at combined kidney and tumor segmentation, this
work proposes a novel combination of 3D U-Nets---collectively denoted
TuNet---utilizing the resulting kidney masks for the consecutive tumor
segmentation. The proposed method achieves a S{\o}rensen-Dice coefficient score
of 0.902 for the kidney, and 0.408 for the tumor segmentation, computed from a
five-fold cross-validation on the 210 patients available in the data.

20
The categories of this paper are: acc-phys
3
The categories of this paper are: physics
15
The categories of this paper are: nucl-ex
17
The categories of this paper are: q-fin
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
9
The categories of this paper are: nlin
4
The categories of this paper are: cond-mat
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
27
The categories of this paper are: comp-gas
25
The categories of this paper are: patt-sol
34
The categories of this paper are: chem-ph