Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: ASL to PET Translation by a Semi-supervised Residual-based
  Attention-guided Convolutional Neural Network   Positron Emission Tomography (PET) is an imaging method that can assess
physiological function rather than structural disturbances by measuring
cerebral perfusion or glucose consumption. However, this imaging technique
relies on injection of radioactive tracers and is expensive. On the contrary,
Arterial Spin Labeling (ASL) MRI is a non-invasive, non-radioactive, and
relatively cheap imaging technique for brain hemodynamic measurements, which
allows quantification to some extent. In this paper we propose a convolutional
neural network (CNN) based model for translating ASL to PET images, which could
benefit patients as well as the healthcare system in terms of expenses and
adverse side effects. However, acquiring a sufficient number of paired ASL-PET
scans for training a CNN is prohibitive for many reasons. To tackle this
problem, we present a new semi-supervised multitask CNN which is trained on
both paired data, i.e. ASL and PET scans, and unpaired data, i.e. only ASL
scans, which alleviates the problem of training a network on limited paired
data. Moreover, we present a new residual-based-attention guided mechanism to
improve the contextual features during the training process. Also, we show that
incorporating T1-weighted scans as an input, due to its high resolution and
availability of anatomical information, improves the results. We performed a
two-stage evaluation based on quantitative image metrics by conducting a 7-fold
cross validation followed by a double-blind observer study. The proposed
network achieved structural similarity index measure (SSIM), mean squared error
(MSE) and peak signal-to-noise ratio (PSNR) values of $0.85\pm0.08$,
$0.01\pm0.01$, and $21.8\pm4.5$ respectively, for translating from 2D ASL and
T1-weighted images to PET data. The proposed model is publicly available via
https://github.com/yousefis/ASL2PET.

12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
32
The categories of this paper are: atom-ph
16
The categories of this paper are: stat
21
The categories of this paper are: adap-org
17
The categories of this paper are: q-fin
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
4
The categories of this paper are: cond-mat