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Proceedings Paper

Three-dimensional image registration of MR proximal femur images for the analysis of trabecular bone parameters
Author(s): Janet Blumenfeld; Colin Studholme; Julio Carballido-Gamio; Thomas M. Link; Sharmila Majumdar
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Paper Abstract

This study investigated the feasibility of automatic image registration of MR high-spatial resolution proximal femur trabecular bone images as well as the effects of gray-level interpolation and volume of interest (VOI) misalignment on MR-derived trabecular bone structure parameters. For six subjects, a baseline scan and a follow-up scan of the proximal femur were acquired on the same day. An automatic image registration technique, based on mutual information, utilized a baseline and a follow-up scan to compute transform parameters that aligned the two images. These parameters were subsequently used to transform the follow-up image with three different gray-level interpolators. Nearest neighbor interpolation and b-spline approximation did not significantly alter bone parameters, while linear interpolation significantly modified bone parameters (p<0.01). Improvement in image alignment due to the automatic registration was determined by visually inspecting difference images and 3D renderings. This work demonstrates the first application of automatic registration, without prior segmentation, of high-spatial resolution trabecular bone MR images of the proximal femur. Additionally, effects due to imprecise analysis volume alignment are investigated. Inherent heterogeneity in trabecular bone structure and imprecise positioning of the VOI along the slice (A/P) direction resulted in significant changes in bone parameters (p<0.01). Results suggest that automatic mutual information registration using nearest-neighbor gray-level interpolation to transform the final image ensures VOI alignment between baseline and follow-up images and does not compromise the integrity of MR-derived trabecular bone parameters.

Paper Details

Date Published: 26 March 2008
PDF: 9 pages
Proc. SPIE 6914, Medical Imaging 2008: Image Processing, 69140G (26 March 2008); doi: 10.1117/12.770460
Show Author Affiliations
Janet Blumenfeld, Univ. of California, San Francisco (United States)
UCSF-UCB Joint Graduate Group in Bioengineering (United States)
Colin Studholme, Univ. of California, San Francisco (United States)
Julio Carballido-Gamio, Univ. of California, San Francisco (United States)
Thomas M. Link, Univ. of California, San Francisco (United States)
Sharmila Majumdar, Univ. of California, San Francisco (United States)

Published in SPIE Proceedings Vol. 6914:
Medical Imaging 2008: Image Processing
Joseph M. Reinhardt; Josien P. W. Pluim, Editor(s)

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