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Proceedings Paper

Adaptive deformable image registration of inhomogeneous tissues
Author(s): Jing Ren
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Paper Abstract

Physics based deformable registration can provide physically consistent image match of deformable soft tissues. In order to help radiologist/surgeons to determine the status of malicious tumors, we often need to accurately align the regions with embedded tumors. This is a very challenging task since the tumor and the surrounding tissues have very different tissue properties such as stiffness and elasticity. In order to address this problem, based on minimum strain energy principle in elasticity theory, we propose to partition the whole region of interest into smaller sub-regions and dynamically adjust weights of vessel segments and bifurcation points in each sub-region in the registration objective function. Our previously proposed fast vessel registration is used as a component in the inner loop. We have validated the proposed method using liver MR images from human subjects. The results show that our method can detect the large registration errors and improve the registration accuracy in the neighborhood of the tumors and guarantee the registration errors to be within acceptable accuracy. The proposed technique has the potential to significantly improve the registration capability and the quality of clinical diagnosis and treatment planning.

Paper Details

Date Published: 18 March 2015
PDF: 6 pages
Proc. SPIE 9415, Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling, 94150S (18 March 2015); doi: 10.1117/12.2082487
Show Author Affiliations
Jing Ren, Univ. of Ontario Institute of Technology (Canada)


Published in SPIE Proceedings Vol. 9415:
Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling
Robert J. Webster; Ziv R. Yaniv, Editor(s)

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