@inproceedings{82f0b660783843878d68ed5c515bd11e,
title = "Automatic quality control of cardiac MRI segmentation in large-scale population imaging",
abstract = "The trend towards large-scale studies including population imaging poses new challenges in terms of quality control (QC). This is a particular issue when automatic processing tools such as image segmentation methods are employed to derive quantitative measures or biomarkers for further analyses. Manual inspection and visual QC of each segmentation result is not feasible at large scale. However, it is important to be able to detect when an automatic method fails to avoid inclusion of wrong measurements into subsequent analyses which could otherwise lead to incorrect conclusions. To overcome this challenge, we explore an approach for predicting segmentation quality based on reverse classification accuracy, which enables us to discriminate between successful and failed cases. We validate this approach on a large cohort of cardiac MRI for which manual QC scores were available. Our results on 7,425 cases demonstrate the potential for fully automatic QC in the context of large-scale population imaging such as the UK Biobank Imaging Study.",
author = "Robert Robinson and Valindria, {Vanya V.} and Wenjia Bai and Hideaki Suzuki and Matthews, {Paul M.} and Chris Page and Daniel Rueckert and Ben Glocker",
note = "Funding Information: Acknowledgements. RR is funded by GSK and EPSRC CDT in Medical Imaging (EP/L015226/1); VV by Indonesia Endowment for Education (LPDP) Indonesian Presidential PhD Scholarship; HS by Research Fellowship from Uehara Memorial Foundation; PMM acknowledges support of Imperial Healthcare Trust BRC, EPSRC Centre for Mathematics in Precision Healthcare and MRC. Publisher Copyright: {\textcopyright} 2017, Springer International Publishing AG.; 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017 ; Conference date: 11-09-2017 Through 13-09-2017",
year = "2017",
doi = "10.1007/978-3-319-66182-7_82",
language = "English",
isbn = "9783319661810",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "720--727",
editor = "Maxime Descoteaux and Simon Duchesne and Alfred Franz and Pierre Jannin and Collins, {D. Louis} and Lena Maier-Hein",
booktitle = "Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings",
}