Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatic Segmentation and Overall Survival Prediction in Gliomas using
  Fully Convolutional Neural Network and Texture Analysis   In this paper, we use a fully convolutional neural network (FCNN) for the
segmentation of gliomas from Magnetic Resonance Images (MRI). A fully
automatic, voxel based classification was achieved by training a 23 layer deep
FCNN on 2-D slices extracted from patient volumes. The network was trained on
slices extracted from 130 patients and validated on 50 patients. For the task
of survival prediction, texture and shape based features were extracted from T1
post contrast volume to train an XGBoost regressor. On BraTS 2017 validation
set, the proposed scheme achieved a mean whole tumor, tumor core and active
dice score of 0.83, 0.69 and 0.69 respectively and an accuracy of 52% for the
overall survival prediction.

16
The categories of this paper are: stat
11
The categories of this paper are: hep-lat
35
The categories of this paper are: mtrl-th
18
The categories of this paper are: econ
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
32
The categories of this paper are: atom-ph
3
The categories of this paper are: physics
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol