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Proceedings Paper

Surface-based 3D image registration using the iterative closest-point algorithm with a closest-point transform
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Paper Abstract

Image registration is a valuable technique for medical diagnosis and treatment. It allows physicians to combine information from multiple images by aligning them into the same coordinate space. Surface-based methods register images by aligning corresponding surfaces of one or more anatomical structures such as the surface of the brain or skull. In this paper we examine a novel implementation of this approach. We use the iterative closest point algorithm to iteratively search for the transformation that minimizes the distance between surface points in one image and a surface model in the other image. In each iteration we use the closest point transform to find corresponding points that are closest with respect to the transformation estimated in the previous iteration. Results from several experiments are presented to demonstrate the efficacy of this approach.

Paper Details

Date Published: 16 April 1996
PDF: 10 pages
Proc. SPIE 2710, Medical Imaging 1996: Image Processing, (16 April 1996); doi: 10.1117/12.237938
Show Author Affiliations
Yaorong Ge, Bowman Gray School of Medicine/Wake Forest Univ. (United States)
Calvin R. Maurer Jr., Vanderbilt Univ. (United States)
J. Michael Fitzpatrick, Vanderbilt Univ. (United States)

Published in SPIE Proceedings Vol. 2710:
Medical Imaging 1996: Image Processing
Murray H. Loew; Kenneth M. Hanson, Editor(s)

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