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A comprehensive approach for learning-based fully-automated inter-slice motion correction for short-axis cine cardiac MR image stacks

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Title: A comprehensive approach for learning-based fully-automated inter-slice motion correction for short-axis cine cardiac MR image stacks
Authors: Tarroni, G
Oktay, O
Sinclair, M
Bai, W
Schuh, A
Suzuki, H
De Marvao, A
O'Regan, D
Cook, S
Rueckert, D
Item Type: Conference Paper
Abstract: In the clinical routine, short axis (SA) cine cardiac MR (CMR) image stacks are acquired during multiple subsequent breath-holds. If the patient cannot consistently hold the breath at the same position, the acquired image stack will be affected by inter-slice respiratory motion and will not correctly represent the cardiac volume, introducing potential errors in the following analyses and visualisations. We propose an approach to automatically correct inter-slice respiratory motion in SA CMR image stacks. Our approach makes use of probabilistic segmentation maps (PSMs) of the left ventricular (LV) cavity generated with decision forests. PSMs are generated for each slice of the SA stack and rigidly registered in-plane to a target PSM. If long axis (LA) images are available, PSMs are generated for them and combined to create the target PSM; if not, the target PSM is produced from the same stack using a 3D model trained from motion-free stacks. The proposed approach was tested on a dataset of SA stacks acquired from 24 healthy subjects (for which anatomical 3D cardiac images were also available as reference) and compared to two techniques which use LA intensity images and LA segmentations as targets, respectively. The results show the accuracy and robustness of the proposed approach in motion compensation.
Editors: Frangi, AF
Schnabel, JA
Davatzikos, C
AlberolaLopez, C
Fichtinger, G
Issue Date: 26-Sep-2018
Date of Acceptance: 1-Sep-2018
URI: http://hdl.handle.net/10044/1/75876
DOI: 10.1007/978-3-030-00928-1_31
ISBN: 978-3-030-00927-4
ISSN: 0302-9743
Publisher: SPRINGER INTERNATIONAL PUBLISHING AG
Start Page: 268
End Page: 276
Journal / Book Title: MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION - MICCAI 2018, PT I
Volume: 11070
Copyright Statement: © Springer Nature Switzerland AG 2018. The final publication is available at Springer via https://doi.org/10.1007/978-3-030-00928-1_31
Conference Name: 21st International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) / 8th Eurographics Workshop on Visual Computing for Biology and Medicine (VCBM)
Keywords: Science & Technology
Technology
Computer Science, Theory & Methods
Imaging Science & Photographic Technology
Computer Science
FRAMEWORK
Science & Technology
Technology
Computer Science, Theory & Methods
Imaging Science & Photographic Technology
Computer Science
FRAMEWORK
cs.CV
cs.CV
Artificial Intelligence & Image Processing
Publication Status: Published
Start Date: 2018-09-16
Finish Date: 2018-09-20
Conference Place: Granada, SPAIN
Online Publication Date: 2018-09-26
Appears in Collections:Computing
Department of Brain Sciences
Department of Brain Sciences