Multi-atlas segmentation as a graph labelling problem: Application to partially annotated atlas data
Koch LM, Rajchl M, Tong T, Passerat-Palmbach J, Aljabar P, Rueckert D (2015)
Publication Type: Conference contribution
Publication year: 2015
Journal
Publisher: Springer Verlag
Book Volume: 9123
Pages Range: 221-232
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Isle of Skye, GBR
DOI: 10.1007/978-3-319-19992-4_17
Abstract
Manually annotating images for multi-atlas segmentation is an expensive and often limiting factor in reliable automated segmentation of large databases. Segmentation methods requiring only a proportion of each atlas image to be labelled could potentially reduce the workload on expert raters tasked with labelling images. However, exploiting such a database of partially labelled atlases is not possible with state-of-the-art multi-atlas segmentation methods. In this paper we revisit the problem of multi-atlas segmentation and formulate its solution in terms of graph-labelling. Our graphical approach uses a Markov Random Field (MRF) formulation of the problem and constructs a graph connecting atlases and the target image. This provides a unifying framework for label propagation. More importantly, the proposed method can be used for segmentation using only partially labelled atlases. We furthermore provide an extension to an existing continuous MRF optimisation method to solve the proposed problem formulation. We show that the proposed method, applied to hippocampal segmentation of 202 subjects from the ADNI database, remains robust and accurate even when the proportion of manually labelled slices in the atlases is reduced to 20 %.
Involved external institutions
United Kingdom (GB)How to cite
APA:
Koch, L.M., Rajchl, M., Tong, T., Passerat-Palmbach, J., Aljabar, P., & Rueckert, D. (2015). Multi-atlas segmentation as a graph labelling problem: Application to partially annotated atlas data. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 221-232). Isle of Skye, GBR: Springer Verlag.
MLA:
Koch, Lisa M., et al. "Multi-atlas segmentation as a graph labelling problem: Application to partially annotated atlas data." Proceedings of the 24th International Conference on Information Processing in Medical Imaging, IPMI 2015, Isle of Skye, GBR Springer Verlag, 2015. 221-232.
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