Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Learning using K-space Based Data Augmentation for Automated
  Cardiac MR Motion Artefact Detection   Quality assessment of medical images is essential for complete automation of
image processing pipelines. For large population studies such as the UK
Biobank, artefacts such as those caused by heart motion are problematic and
manual identification is tedious and time-consuming. Therefore, there is an
urgent need for automatic image quality assessment techniques. In this paper,
we propose a method to automatically detect the presence of motion-related
artefacts in cardiac magnetic resonance (CMR) images. As this is a highly
imbalanced classification problem (due to the high number of good quality
images compared to the low number of images with motion artefacts), we propose
a novel k-space based training data augmentation approach in order to address
this problem. Our method is based on 3D spatio-temporal Convolutional Neural
Networks, and is able to detect 2D+time short axis images with motion artefacts
in less than 1ms. We test our algorithm on a subset of the UK Biobank dataset
consisting of 3465 CMR images and achieve not only high accuracy in detection
of motion artefacts, but also high precision and recall. We compare our
approach to a range of state-of-the-art quality assessment methods.

37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
25
The categories of this paper are: patt-sol
3
The categories of this paper are: physics
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
13
The categories of this paper are: quant-ph
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
26
The categories of this paper are: bayes-an
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
0
The categories of this paper are: hep-ph