DocumentCode :
3603009
Title :
Statistical Biomechanical Surface Registration: Application to MR-TRUS Fusion for Prostate Interventions
Author :
Khallaghi, Siavash ; Sanchez, C. Antonio ; Rasoulian, Abtin ; Nouranian, Saman ; Romagnoli, Cesare ; Abdi, Hamidreza ; Chang, Silvia D. ; Black, Peter C. ; Goldenberg, Larry ; Morris, William J. ; Spadinger, Ingrid ; Fenster, Aaron ; Ward, Aaron ; Fels, S
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of British Columbia, Vancouver, BC, Canada
Volume :
34
Issue :
12
fYear :
2015
Firstpage :
2535
Lastpage :
2549
Abstract :
A common challenge when performing surface-based registration of images is ensuring that the surfaces accurately represent consistent anatomical boundaries. Image segmentation may be difficult in some regions due to either poor contrast, low slice resolution, or tissue ambiguities. To address this, we present a novel non-rigid surface registration method designed to register two partial surfaces, capable of ignoring regions where the anatomical boundary is unclear. Our probabilistic approach incorporates prior geometric information in the form of a statistical shape model (SSM), and physical knowledge in the form of a finite element model (FEM). We validate results in the context of prostate interventions by registering pre-operative magnetic resonance imaging (MRI) to 3D transrectal ultrasound (TRUS). We show that both the geometric and physical priors significantly decrease net target registration error (TRE), leading to TREs of 2.35 ± 0.81 mm and 2.81 ± 0.66 mm when applied to full and partial surfaces, respectively. We investigate robustness in response to errors in segmentation, varying levels of missing data, and adjusting the tunable parameters. Results demonstrate that the proposed surface registration method is an efficient, robust, and effective solution for fusing data from multiple modalities.
Keywords :
biological organs; biological tissues; biomechanics; biomedical MRI; biomedical ultrasonics; finite element analysis; image fusion; image registration; image segmentation; probability; statistical analysis; 3D transrectal ultrasound; FEM; MR-TRUS fusion; anatomical boundary; finite element model; image segmentation; nonrigid surface registration method; partial surface registration; preoperative magnetic resonance imaging; probabilistic approach; prostate interventions; slice resolution; statistical biomechanical surface registration; statistical shape model; target registration error; tissue ambiguity; Computational modeling; Deformable models; Finite element analysis; Image segmentation; Mathematical model; Shape; Transforms; Biopsy; finite element modeling; gaussian mixture model; prostate; statistical shape model; surface registration;
fLanguage :
English
Journal_Title :
Medical Imaging, IEEE Transactions on
Publisher :
ieee
ISSN :
0278-0062
Type :
jour
DOI :
10.1109/TMI.2015.2443978
Filename :
7122311
Link To Document :
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