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Proceedings Paper

Constrained non-rigid registration for whole body image registration: method and validation
Author(s): Xia Li; Thomas E. Yankeelov; Todd E. Peterson; John C. Gore; Benoit M. Dawant
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Paper Abstract

3D intra- and inter-subject registration of image volumes is important for tasks that include measurements and quantification of temporal/longitudinal changes, atlas-based segmentation, deriving population averages, or voxel and tensor-based morphometry. A number of methods have been proposed to tackle this problem but few of them have focused on the problem of registering whole body image volumes acquired either from humans or small animals. These image volumes typically contain a large number of articulated structures, which makes registration more difficult than the registration of head images, to which the vast majority of registration algorithms have been applied. To solve this problem, we have previously proposed an approach, which initializes an intensity-based non-rigid registration algorithm with a point based registration technique [1, 2]. In this paper, we introduce new constraints into our non-rigid registration algorithm to prevent the bones from being deformed inaccurately. Results we have obtained show that the new constrained algorithm leads to better registration results than the previous one.

Paper Details

Date Published: 1 March 2007
PDF: 8 pages
Proc. SPIE 6512, Medical Imaging 2007: Image Processing, 651202 (1 March 2007); doi: 10.1117/12.709026
Show Author Affiliations
Xia Li, Vanderbilt Univ. (United States)
Thomas E. Yankeelov, Vanderbilt Univ. Institute of Imaging Science (United States)
Todd E. Peterson, Vanderbilt Univ. Institute of Imaging Science (United States)
John C. Gore, Vanderbilt Univ. Institute of Imaging Science (United States)
Benoit M. Dawant, Vanderbilt Univ. (United States)

Published in SPIE Proceedings Vol. 6512:
Medical Imaging 2007: Image Processing
Josien P. W. Pluim; Joseph M. Reinhardt, Editor(s)

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