A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation

Wouter M. Kouw; Silas N. Ørting; Jens Petersen; Kim S. Pedersen; Marleen de Bruijne

doi:10.1007/978-3-030-20351-1_27

A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation

Wouter M. Kouw^*, Silas N. Ørting, Jens Petersen, Kim S. Pedersen, Marleen de Bruijne

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

9 Citations (Scopus)

Abstract

Suppose one is faced with the challenge of tissue segmentation in MR images, without annotators at their center to provide labeled training data. One option is to go to another medical center for a trained classifier. Sadly, tissue classifiers do not generalize well across centers due to voxel intensity shifts caused by center-specific acquisition protocols. However, certain aspects of segmentations, such as spatial smoothness, remain relatively consistent and can be learned separately. Here we present a smoothness prior that is fit to segmentations produced at another medical center. This informative prior is presented to an unsupervised Bayesian model. The model clusters the voxel intensities, such that it produces segmentations that are similarly smooth to those of the other medical center. In addition, the unsupervised Bayesian model is extended to a semi-supervised variant, which needs no visual interpretation of clusters into tissues.

Original language	English
Title of host publication	Information Processing in Medical Imaging : 26th International Conference, IPMI 2019, Proceedings
Editors	Siqi Bao, Albert C.S. Chung, James C. Gee, Paul A. Yushkevich
Publisher	Springer
Publication date	1 Jan 2019
Pages	360-371
ISBN (Print)	9783030203504
DOIs	https://doi.org/10.1007/978-3-030-20351-1_27
Publication status	Published - 1 Jan 2019
Event	26th International Conference on Information Processing in Medical Imaging, IPMI 2019 - Hong Kong, China Duration: 2 Jun 2019 → 7 Jun 2019

Conference

Conference	26th International Conference on Information Processing in Medical Imaging, IPMI 2019
Country/Territory	China
City	Hong Kong
Period	02/06/2019 → 07/06/2019

Series	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11492 LNCS
ISSN	0302-9743

Keywords

Bayesian transfer learning
Image segmentation
Variational inference

Access to Document

10.1007/978-3-030-20351-1_27

http://arxiv.org/pdf/1903.04191

Cite this

Kouw, W. M., Ørting, S. N., Petersen, J., Pedersen, K. S., & de Bruijne, M. (2019). A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation. In S. Bao, A. C. S. Chung, J. C. Gee, & P. A. Yushkevich (Eds.), Information Processing in Medical Imaging : 26th International Conference, IPMI 2019, Proceedings (pp. 360-371). Springer. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 11492 LNCS https://doi.org/10.1007/978-3-030-20351-1_27

A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation. / Kouw, Wouter M.; Ørting, Silas N.; Petersen, Jens ; Pedersen, Kim S.; de Bruijne, Marleen.

Information Processing in Medical Imaging : 26th International Conference, IPMI 2019, Proceedings. ed. / Siqi Bao; Albert C.S. Chung; James C. Gee; Paul A. Yushkevich. Springer, 2019. p. 360-371 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11492 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Kouw, WM, Ørting, SN, Petersen, J , Pedersen, KS & de Bruijne, M 2019, A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation. in S Bao, ACS Chung, JC Gee & PA Yushkevich (eds), Information Processing in Medical Imaging : 26th International Conference, IPMI 2019, Proceedings. Springer, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11492 LNCS, pp. 360-371, 26th International Conference on Information Processing in Medical Imaging, IPMI 2019, Hong Kong, China, 02/06/2019. https://doi.org/10.1007/978-3-030-20351-1_27

Kouw WM, Ørting SN, Petersen J , Pedersen KS , de Bruijne M. A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation. In Bao S, Chung ACS, Gee JC, Yushkevich PA, editors, Information Processing in Medical Imaging : 26th International Conference, IPMI 2019, Proceedings. Springer. 2019. p. 360-371. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11492 LNCS). https://doi.org/10.1007/978-3-030-20351-1_27

Kouw, Wouter M. ; Ørting, Silas N. ; Petersen, Jens ; Pedersen, Kim S. ; de Bruijne, Marleen. / A Cross-Center Smoothness Prior for Variational Bayesian Brain Tissue Segmentation. Information Processing in Medical Imaging : 26th International Conference, IPMI 2019, Proceedings. editor / Siqi Bao ; Albert C.S. Chung ; James C. Gee ; Paul A. Yushkevich. Springer, 2019. pp. 360-371 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 11492 LNCS).

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