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Detection and correction of cardiac MRI motion artefacts during reconstruction from k-space

Oksuz I, Clough J, Ruijsink B, Puyol-Anton E, Bustin A, Cruz G, Prieto C, Rueckert D, King AP, Schnabel JA (2019)

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Publication Type: Conference contribution

Publication year: 2019

Journal

Publisher: Springer Science and Business Media Deutschland GmbH

Book Volume: 11767 LNCS

Pages Range: 695-703

Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Event location: Shenzhen, CHN

ISBN: 9783030322502

DOI: 10.1007/978-3-030-32251-9_76

Abstract

In fully sampled cardiac MR (CMR) acquisitions, motion can lead to corruption of k-space lines, which can result in artefacts in the reconstructed images. In this paper, we propose a method to automatically detect and correct motion-related artefacts in CMR acquisitions during reconstruction from k-space data. Our correction method is inspired by work on undersampled CMR reconstruction, and uses deep learning to optimize a data-consistency term for under-sampled k-space reconstruction. Our main methodological contribution is the addition of a detection network to classify motion-corrupted k-space lines to convert the problem of artefact correction to a problem of reconstruction using the data consistency term. We train our network to automatically correct for motion-related artefacts using synthetically corrupted cine CMR k-space data as well as uncorrupted CMR images. Using a test set of 50 2D+time cine CMR datasets from the UK Biobank, we achieve good image quality in the presence of synthetic motion artefacts. We quantitatively compare our method with a variety of techniques for recovering good image quality and showcase better performance compared to state of the art denoising techniques with a PSNR of 37.1. Moreover, we show that our method preserves the quality of uncorrupted images and therefore can be also utilized as a general image reconstruction algorithm.

Involved external institutions

How to cite

APA:

Oksuz, I., Clough, J., Ruijsink, B., Puyol-Anton, E., Bustin, A., Cruz, G.,... Schnabel, J.A. (2019). Detection and correction of cardiac MRI motion artefacts during reconstruction from k-space. In Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 695-703). Shenzhen, CHN: Springer Science and Business Media Deutschland GmbH.

MLA:

Oksuz, Ilkay, et al. "Detection and correction of cardiac MRI motion artefacts during reconstruction from k-space." Proceedings of the 22nd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2019, Shenzhen, CHN Ed. Dinggang Shen, Pew-Thian Yap, Tianming Liu, Terry M. Peters, Ali Khan, Lawrence H. Staib, Caroline Essert, Sean Zhou, Springer Science and Business Media Deutschland GmbH, 2019. 695-703.

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