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Proceedings Paper

Optimizing nonrigid registration performance between volumetric true 3D ultrasound images in image-guided neurosurgery
Author(s): Songbai Ji; Xiaoyao Fan; David W. Roberts; Alex Hartov; Keith D. Paulsen
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Paper Abstract

Compensating for brain shift as surgery progresses is important to ensure sufficient accuracy in patient-to-image registration in the operating room (OR) for reliable neuronavigation. Ultrasound has emerged as an important and practical imaging technique for brain shift compensation either by itself or through computational modeling that estimates whole-brain deformation. Using volumetric true 3D ultrasound (3DUS), it is possible to nonrigidly (e.g., based on B-splines) register two temporally different 3DUS images directly to generate feature displacement maps for data assimilation in the biomechanical model. Because of a large amount of data and number of degrees-of-freedom (DOFs) involved, however, a significant computational cost may be required that can adversely influence the clinical feasibility of the technique for efficiently generating model-updated MR (uMR) in the OR. This paper parametrically investigates three B-splines registration parameters and their influence on the computational cost and registration accuracy: number of grid nodes along each direction, floating image volume down-sampling rate, and number of iterations. A simulated rigid body displacement field was employed as a ground-truth against which the accuracy of displacements generated from the B-splines nonrigid registration was compared. A set of optimal parameters was then determined empirically that result in a registration computational cost of less than 1 min and a sub-millimetric accuracy in displacement measurement. These resulting parameters were further applied to a clinical surgery case to demonstrate their practical use. Our results indicate that the optimal set of parameters result in sufficient accuracy and computational efficiency in model computation, which is important for future application of the overall biomechanical modeling to generate uMR for image-guidance in the OR.

Paper Details

Date Published: 1 March 2011
PDF: 9 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 79640V (1 March 2011); doi: 10.1117/12.878353
Show Author Affiliations
Songbai Ji, Dartmouth College (United States)
Xiaoyao Fan, Dartmouth College (United States)
David W. Roberts, Dartmouth Hitchcock Medical Ctr. (United States)
Alex Hartov, Dartmouth College (United States)
Dartmouth Hitchcock Medical Ctr. (United States)
Keith D. Paulsen, Dartmouth College (United States)
Dartmouth Hitchcock Medical Ctr. (United States)


Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes III, Editor(s)

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