Hierarchical segmentation-assisted multimodal registration for MR brain images

Lu, Huanxiang; Beisteiner, Roland; Nolte, Lutz-Peter; Reyes, Mauricio (2013). Hierarchical segmentation-assisted multimodal registration for MR brain images. Computerized medical imaging and graphics, 37(3), pp. 234-244. Elsevier 10.1016/j.compmedimag.2013.03.004

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Information theory-based metric such as mutual information (MI) is widely used as similarity measurement for multimodal registration. Nevertheless, this metric may lead to matching ambiguity for non-rigid registration. Moreover, maximization of MI alone does not necessarily produce an optimal solution. In this paper, we propose a segmentation-assisted similarity metric based on point-wise mutual information (PMI). This similarity metric, termed SPMI, enhances the registration accuracy by considering tissue classification probabilities as prior information, which is generated from an expectation maximization (EM) algorithm. Diffeomorphic demons is then adopted as the registration model and is optimized in a hierarchical framework (H-SPMI) based on different levels of anatomical structure as prior knowledge. The proposed method is evaluated using Brainweb synthetic data and clinical fMRI images. Both qualitative and quantitative assessment were performed as well as a sensitivity analysis to the segmentation error. Compared to the pure intensity-based approaches which only maximize mutual information, we show that the proposed algorithm provides significantly better accuracy on both synthetic and clinical data.

Item Type:

Journal Article (Original Article)

Division/Institute:

04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB

UniBE Contributor:

Lu, Huanxiang; Nolte, Lutz-Peter and Reyes, Mauricio

Subjects:

500 Science > 570 Life sciences; biology
600 Technology > 610 Medicine & health
000 Computer science, knowledge & systems

ISSN:

0895-6111

Publisher:

Elsevier

Language:

English

Submitter:

Mauricio Antonio Reyes Aguirre

Date Deposited:

15 Apr 2014 10:52

Last Modified:

15 Jan 2015 15:37

Publisher DOI:

10.1016/j.compmedimag.2013.03.004

Uncontrolled Keywords:

Multimodal non-rigid registration, Tissue classification, EPI distortion correction

BORIS DOI:

10.7892/boris.46460

URI:

https://boris.unibe.ch/id/eprint/46460

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