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Proceedings Paper

Semiautomatic segmentation of textured laser range scans for use in image-guided procedures
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Paper Abstract

Laser range scanners produce high resolution surface data of anatomic structures, which facilitates the determination of intraoperative soft tissue deformation and the performance of surface based image-to-physical space registration. Segmentation of the range scans is required for the data to be effectively incorporated into current image-guided procedures. Due to time constraints in the operating room, manual segmentation methods are not feasible. We propose a novel segmentation algorithm based on the level set method that uses information from the texture map and curvature of the acquired point cloud to provide an accurate edge map for computation of the speed image. Specifically, the edge image is created by combining the curvature values, computed from a surface fitted to the acquired point cloud using radial basis functions, and gradients of the RGB intensities in the texture map. Preliminary results, obtained from comparing the semiautomatic segmentations of intraoperatively acquire liver LRS data with manual gold standard segmentations, shows the method to be a significant first step towards the implementation of semiautomatic LRS segmentation routine during image-guided surgery.

Paper Details

Date Published: 29 April 2005
PDF: 9 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.595814
Show Author Affiliations
Logan W. Clements, Vanderbilt Univ. (United States)
David Marshall Cash, Pathfinder Therapeutics Inc. (United States)
Tuhin K. Sinha, Vanderbilt Univ. (United States)
Robert L. Galloway, Vanderbilt Univ. (United States)


Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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