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Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets

Sinclair M, Bai W, Puyol-Antón E, Oktay O, Rueckert D, King AP (2017)

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Publication Type: Conference contribution

Publication year: 2017

Journal

Publisher: Springer Verlag

Book Volume: 10434 LNCS

Pages Range: 332-340

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

Event location: Quebec City, QC, CAN

ISBN: 9783319661841

DOI: 10.1007/978-3-319-66185-8_38

Abstract

Cardiac magnetic resonance (CMR) can be used for quantitative analysis of heart function. However, CMR imaging typically involves acquiring 2D image planes during separate breath-holds, often resulting in misalignment of the heart between image planes in 3D. Accurate quantitative analysis requires a robust 3D reconstruction of the heart from CMR images, which is adversely affected by such motion artifacts. Therefore, we propose a fully automated method for motion correction of CMR planes using segmentations produced by fully convolutional neural networks (FCNs). FCNs are trained on 100 UK Biobank subjects to produce short-axis and long-axis segmentations, which are subsequently used in an iterative registration algorithm for correcting breath-hold induced motion artifacts. We demonstrate significant improvements in motion-correction over image-based registration, with strong correspondence to results obtained using manual segmentations. We also deploy our automatic method on 9,353 subjects in the UK Biobank database, demonstrating significant improvements in 3D plane alignment.

Involved external institutions

How to cite

APA:

Sinclair, M., Bai, W., Puyol-Antón, E., Oktay, O., Rueckert, D., & King, A.P. (2017). Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets. In Pierre Jannin, Simon Duchesne, Maxime Descoteaux, Alfred Franz, D. Louis Collins, Lena Maier-Hein (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 332-340). Quebec City, QC, CAN: Springer Verlag.

MLA:

Sinclair, Matthew, et al. "Fully automated segmentation-based respiratory motion correction of multiplanar cardiac magnetic resonance images for large-scale datasets." Proceedings of the 20th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2017, Quebec City, QC, CAN Ed. Pierre Jannin, Simon Duchesne, Maxime Descoteaux, Alfred Franz, D. Louis Collins, Lena Maier-Hein, Springer Verlag, 2017. 332-340.

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