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Proceedings Paper

Nonrigid liver registration for image-guided surgery using partial surface data: a novel iterative approach
Author(s): D. Caleb Rucker; Yifei Wu; Janet E. Ondrake; Thomas S. Pheiffer; Amber L. Simpson; Michael I. Miga
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Paper Abstract

In the context of open abdominal image-guided liver surgery, the efficacy of an image-guidance system relies on its ability to (1) accurately depict tool locations with respect to the anatomy, and (2) maintain the work flow of the surgical team. Laser-range scanned (LRS) partial surface measurements can be taken intraoperatively with relatively little impact on the surgical work flow, as opposed to other intraoperative imaging modalities. Previous research has demonstrated that this kind of partial surface data may be (1) used to drive a rigid registration of the preoperative CT image volume to intraoperative patient space, and (2) extrapolated and combined with a tissue-mechanics-based organ model to drive a non-rigid registration, thus compensating for organ deformations. In this paper we present a novel approach for intraoperative nonrigid liver registration which iteratively reconstructs a displacement field on the posterior side of the organ in order to minimize the error between the deformed model and the intraopreative surface data. Experimental results with a phantom liver undergoing large deformations demonstrate that this method achieves target registration errors (TRE) with a mean of 4.0 mm in the prediction of a set of 58 locations inside the phantom, which represents a 50% improvement over rigid registration alone, and a 44% improvement over the prior non-iterative single-solve method of extrapolating boundary conditions via a surface Laplacian.

Paper Details

Date Published: 8 March 2013
PDF: 6 pages
Proc. SPIE 8671, Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling, 86710B (8 March 2013); doi: 10.1117/12.2007991
Show Author Affiliations
D. Caleb Rucker, Vanderbilt Univ. (United States)
Yifei Wu, Vanderbilt Univ. (United States)
Janet E. Ondrake, Vanderbilt Univ. (United States)
Thomas S. Pheiffer, Vanderbilt Univ. (United States)
Amber L. Simpson, Vanderbilt Univ. (United States)
Michael I. Miga, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 8671:
Medical Imaging 2013: Image-Guided Procedures, Robotic Interventions, and Modeling
David R. Holmes; Ziv R. Yaniv, Editor(s)

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