Multi-atlas spectral PatchMatch: Application to cardiac image segmentation
Shi W, Lombaert H, Bai W, Ledig C, Zhuang X, Marvao A, Dawes T, O'Regan D, Rueckert D (2014)
Publication Type: Conference contribution
Publication year: 2014
Journal
Publisher: Springer Verlag
Book Volume: 8673 LNCS
Pages Range: 348-355
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: USA
ISBN: 9783319104034
DOI: 10.1007/978-3-319-10404-1_44
Abstract
The automatic segmentation of cardiac magnetic resonance images poses many challenges arising from the large variation between different anatomies, scanners and acquisition protocols. In this paper, we address these challenges with a global graph search method and a novel spectral embedding of the images. Firstly, we propose the use of an approximate graph search approach to initialize patch correspondences between the image to be segmented and a database of labelled atlases. Then, we propose an innovative spectral embedding using a multi-layered graph of the images in order to capture global shape properties. Finally, we estimate the patch correspondences based on a joint spectral representation of the image and atlases. We evaluated the proposed approach using 155 images from the recent MICCAI SATA segmentation challenge and demonstrated that the proposed algorithm significantly outperforms current state-of-the-art methods on both training and test sets. © 2014 Springer International Publishing.
Involved external institutions
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
Inria
France (FR)
Chinese Academy of Sciences (CAS) / 中国科学院
China (CN)
United Kingdom (GB)
Inria
France (FR)
Chinese Academy of Sciences (CAS) / 中国科学院
China (CN)
How to cite
APA:
Shi, W., Lombaert, H., Bai, W., Ledig, C., Zhuang, X., Marvao, A.,... Rueckert, D. (2014). Multi-atlas spectral PatchMatch: Application to cardiac image segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 348-355). USA: Springer Verlag.
MLA:
Shi, Wenzhe, et al. "Multi-atlas spectral PatchMatch: Application to cardiac image segmentation." Proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, USA Springer Verlag, 2014. 348-355.
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