Efficient multi-atlas registration using an intermediate template image

Blake E. Dewey; Aaron Carass; Ari M. Blitz; Jerry L. Prince

doi:10.1117/12.2256147

13 March 2017 Efficient multi-atlas registration using an intermediate template image

Blake E. Dewey, Aaron Carass, Ari M. Blitz, Jerry L. Prince

Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101371F (2017) https://doi.org/10.1117/12.2256147
Event: SPIE Medical Imaging, 2017, Orlando, Florida, United States

Abstract

Multi-atlas label fusion is an accurate but time-consuming method of labeling the human brain. Using an intermediate image as a registration target can allow researchers to reduce time constraints by storing the deformations required of the atlas images. In this paper, we investigate the effect of registration through an intermediate template image on multi-atlas label fusion and propose a novel registration technique to counteract the negative effects of through-template registration. We show that overall computation time can be decreased dramatically with minimal impact on final label accuracy and time can be exchanged for improved results in a predictable manner. We see almost complete recovery of Dice similarity over a simple through-template registration using the corrected method and still maintain a 3-4 times speed increase. Further, we evaluate the effectiveness of this method on brains of patients with normal-pressure hydrocephalus, where abnormal brain shape presents labeling difficulties, specifically the ventricular labels. Our correction method creates substantially better ventricular labeling than traditional methods and maintains the speed increase seen in healthy subjects.

Conference Presentation

Citation Download Citation

Blake E. Dewey, Aaron Carass, Ari M. Blitz, and Jerry L. Prince "Efficient multi-atlas registration using an intermediate template image", Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101371F (13 March 2017); https://doi.org/10.1117/12.2256147

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