Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Ensemble CNN Networks for GBM Tumors Segmentation using Multi-parametric
  MRI   Glioblastomas are the most aggressive fast-growing primary brain cancer which
originate in the glial cells of the brain. Accurate identification of the
malignant brain tumor and its sub-regions is still one of the most challenging
problems in medical image segmentation. The Brain Tumor Segmentation Challenge
(BraTS) has been a popular benchmark for automatic brain glioblastomas
segmentation algorithms since its initiation. In this year, BraTS 2021
challenge provides the largest multi-parametric (mpMRI) dataset of 2,000
pre-operative patients. In this paper, we propose a new aggregation of two deep
learning frameworks namely, DeepSeg and nnU-Net for automatic glioblastoma
recognition in pre-operative mpMRI. Our ensemble method obtains Dice similarity
scores of 92.00, 87.33, and 84.10 and Hausdorff Distances of 3.81, 8.91, and
16.02 for the enhancing tumor, tumor core, and whole tumor regions,
respectively, on the BraTS 2021 validation set, ranking us among the top ten
teams. These experimental findings provide evidence that it can be readily
applied clinically and thereby aiding in the brain cancer prognosis, therapy
planning, and therapy response monitoring. A docker image for reproducing our
segmentation results is available online at
(https://hub.docker.com/r/razeineldin/deepseg21).

21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
13
The categories of this paper are: quant-ph
7
The categories of this paper are: hep-th
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
24
The categories of this paper are: dg-ga
25
The categories of this paper are: patt-sol
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph