Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Bifurcated Autoencoder for Segmentation of COVID-19 Infected Regions in
  CT Images   The new coronavirus infection has shocked the world since early 2020 with its
aggressive outbreak. Rapid detection of the disease saves lives, and relying on
medical imaging (Computed Tomography and X-ray) to detect infected lungs has
shown to be effective. Deep learning and convolutional neural networks have
been used for image analysis in this context. However, accurate identification
of infected regions has proven challenging for two main reasons. Firstly, the
characteristics of infected areas differ in different images. Secondly,
insufficient training data makes it challenging to train various machine
learning algorithms, including deep-learning models. This paper proposes an
approach to segment lung regions infected by COVID-19 to help cardiologists
diagnose the disease more accurately, faster, and more manageable. We propose a
bifurcated 2-D model for two types of segmentation. This model uses a shared
encoder and a bifurcated connection to two separate decoders. One decoder is
for segmentation of the healthy region of the lungs, while the other is for the
segmentation of the infected regions. Experiments on publically available
images show that the bifurcated structure segments infected regions of the
lungs better than state of the art.

37
The categories of this paper are: supr-con
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
36
The categories of this paper are: cmp-lg
34
The categories of this paper are: chem-ph
29
The categories of this paper are: funct-an
32
The categories of this paper are: atom-ph
24
The categories of this paper are: dg-ga
7
The categories of this paper are: hep-th
6
The categories of this paper are: astro-ph
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
8
The categories of this paper are: hep-ex