Publications from our Researchers

Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.  

Citation

BibTex format

@article{Tarroni:2020,
author = {Tarroni, G and Bai, W and Oktay, O and Schuh, A and Suzuki, H and Glocker, B and Matthews, P and Rueckert, D},
journal = {Scientific Reports},
title = {Large-scale quality control of cardiac imaging in population studies: application to UK Biobank},
url = {http://hdl.handle.net/10044/1/76571},
volume = {10},
year = {2020}
}

RIS format (EndNote, RefMan)

TY  - JOUR
AB - In large population studies such as the UK Biobank (UKBB), quality control of the acquired images by visual assessment isunfeasible. In this paper, we apply a recently developed fully-automated quality control pipeline for cardiac MR (CMR) imagesto the first 19,265 short-axis (SA) cine stacks from the UKBB. We present the results for the three estimated quality metrics(heart coverage, inter-slice motion and image contrast in the cardiac region) as well as their potential associations with factorsincluding acquisition details and subject-related phenotypes. Up to 14.2% of the analysed SA stacks had sub-optimal coverage(i.e. missing basal and/or apical slices), however most of them were limited to the first year of acquisition. Up to 16% of thestacks were affected by noticeable inter-slice motion (i.e. average inter-slice misalignment greater than 3.4 mm). Inter-slicemotion was positively correlated with weight and body surface area. Only 2.1% of the stacks had an average end-diastoliccardiac image contrast below 30% of the dynamic range. These findings will be highly valuable for both the scientists involvedin UKBB CMR acquisition and for the ones who use the dataset for research purposes.
AU - Tarroni,G
AU - Bai,W
AU - Oktay,O
AU - Schuh,A
AU - Suzuki,H
AU - Glocker,B
AU - Matthews,P
AU - Rueckert,D
PY - 2020///
SN - 2045-2322
TI - Large-scale quality control of cardiac imaging in population studies: application to UK Biobank
T2 - Scientific Reports
UR - http://hdl.handle.net/10044/1/76571
VL - 10
ER -

Contact us

Data Science Institute

William Penney Laboratory
Imperial College London
South Kensington Campus
London SW7 2AZ
United Kingdom

Email us.

Sign up to our mailing list.

Follow us on Twitter, LinkedIn and Instagram.