Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automated Detection of Cortical Lesions in Multiple Sclerosis Patients
  with 7T MRI   The automated detection of cortical lesions (CLs) in patients with multiple
sclerosis (MS) is a challenging task that, despite its clinical relevance, has
received very little attention. Accurate detection of the small and scarce
lesions requires specialized sequences and high or ultra-high field MRI. For
supervised training based on multimodal structural MRI at 7T, two experts
generated ground truth segmentation masks of 60 patients with 2014 CLs. We
implemented a simplified 3D U-Net with three resolution levels (3D U-Net-). By
increasing the complexity of the task (adding brain tissue segmentation), while
randomly dropping input channels during training, we improved the performance
compared to the baseline. Considering a minimum lesion size of 0.75 {\mu}L, we
achieved a lesion-wise cortical lesion detection rate of 67% and a false
positive rate of 42%. However, 393 (24%) of the lesions reported as false
positives were post-hoc confirmed as potential or definite lesions by an
expert. This indicates the potential of the proposed method to support experts
in the tedious process of CL manual segmentation.

31
The categories of this paper are: ao-sci
7
The categories of this paper are: hep-th
21
The categories of this paper are: adap-org
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
27
The categories of this paper are: comp-gas
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
4
The categories of this paper are: cond-mat
20
The categories of this paper are: acc-phys
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph
5
The categories of this paper are: gr-qc