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Proceedings Paper

An elastic registration framework to estimate prostate deformation in endorectal MR scans
Author(s): Muqing Lin; Vijay Parthasarathy; Harsh K. Agarwal; Peter L. Choyke; Baris Turkbey; Tobias Klinder; Jochen Kruecker
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Paper Abstract

In an effort to improve the accuracy of transrectal ultrasound (TRUS)-guided needle biopsies of the prostate, it is important to understand the non-rigid deformation of the prostate. To understand the deformation of the prostate when an endorectal coil (ERC) is inserted, we develop an elastic registration framework to register prostate MR images with and without ERC. Our registration framework uses robust point matching (RPM) to get the correspondence between the surface landmarks in the source and target volumes followed by elastic body spline (EBS) registration based on the corresponding landmark pairs. Together with the manual rigid alignment, we compared our registration framework based on pure surface landmarks to the registration based on both surface and internal landmarks in the center of the prostate. In addition, we assessed the impact of constraining the warping in the central zone of the prostate using a Gaussian weighting function. Our results show that elastic surface-driven prostate registration is feasible, and that internal landmarks further improve the registration in the central zone while they have little impact on the registration in the peripheral zone of the prostate. Results varied case by case depending on the accuracy of the prostate segmentation and the amount of warping present in each image pair. The most accurate results were obtained when using a Gaussian weighting in the central zone to limit the EBS warping driven by surface points. This suggests that a Gaussian constrain of the warping can effectively compensate for the limitations of the isotropic EBS deformation model, and for erroneous warping inside the prostate created by inaccurate surface landmarks driving the EBS.

Paper Details

Date Published: 17 February 2012
PDF: 8 pages
Proc. SPIE 8316, Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling, 831610 (17 February 2012); doi: 10.1117/12.912353
Show Author Affiliations
Muqing Lin, Philips Research North America (United States)
Vijay Parthasarathy, Philips Research North America (United States)
Harsh K. Agarwal, Philips Research North America (United States)
Peter L. Choyke, National Institutes of Health (United States)
Baris Turkbey, National Institutes of Health (United States)
Tobias Klinder, Philips Research North America (United States)
Jochen Kruecker, Philips Research North America (United States)


Published in SPIE Proceedings Vol. 8316:
Medical Imaging 2012: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes; Kenneth H. Wong, Editor(s)

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