Geodesic patch-based segmentation

Wang Z, Bhatia KK, Glocker B, Marvao A, Dawes T, Misawa K, Mori K, Rueckert D (2014)

Publication Type: Conference contribution

Publication year: 2014

Journal

Lecture Notes in Computer Science Springer Verlag

Publisher: Springer Verlag

Book Volume: 8673 LNCS

Pages Range: 666-673

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_83

Abstract

Label propagation has been shown to be effective in many automatic segmentation applications. However, its reliance on accurate image alignment means that segmentation results can be affected by any registration errors which occur. Patch-based methods relax this dependence by avoiding explicit one-to-one correspondence assumptions between images but are still limited by the search window size. Too small, and it does not account for enough registration error; too big, and it becomes more likely to select incorrect patches of similar appearance for label fusion. This paper presents a novel patch-based label propagation approach which uses relative geodesic distances to define patient-specific coordinate systems as spatial context to overcome this problem. The approach is evaluated on multi-organ segmentation of 20 cardiac MR images and 100 abdominal CT images, demonstrating competitive results. © 2014 Springer International Publishing.

Involved external institutions

Imperial College London / The Imperial College of Science, Technology and Medicine GB United Kingdom (GB) Aichi Cancer Center Research Institute JP Japan (JP) Nagoya University / 名古屋大学 JP Japan (JP)

How to cite

APA:

Wang, Z., Bhatia, K.K., Glocker, B., Marvao, A., Dawes, T., Misawa, K.,... Rueckert, D. (2014). Geodesic patch-based segmentation. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 666-673). USA: Springer Verlag.

MLA:

Wang, Zehan, et al. "Geodesic patch-based segmentation." Proceedings of the 17th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2014, USA Springer Verlag, 2014. 666-673.

BibTeX: Download