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用于分析小梁骨参数的MR近端股骨图像的三维图像配准。

Three-dimensional image registration of MR proximal femur images for the analysis of trabecular bone parameters.

作者信息

Blumenfeld Janet, Studholme Colin, Carballido-Gamio Julio, Carpenter Dana, Link Thomas M, Majumdar Sharmila

机构信息

Department of Radiology and UCSF-UCB Joint Graduate Group in Bioengineering, University of California, San Francisco, San Francisco, California 94107, USA.

出版信息

Med Phys. 2008 Oct;35(10):4630-9. doi: 10.1118/1.2977764.

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 in a short-term study, a baseline scan and a follow-up scan of the proximal femur were acquired on the same day. For ten subjects in a long-term study, a follow-up scan of the proximal femur was acquired 1 year after the baseline. 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. In the short-term study, 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 for the long-term and short-term study was determined by 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, inherent heterogeneity in trabecular bone structure and imprecise positioning of the VOI along the slice (anterior-posterior) direction resulted in significant changes in bone parameters (p<0.01). Results suggest that automatic mutual information registration using B-spline approximation or 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 used in this study.

摘要

本研究调查了磁共振成像(MR)高空间分辨率近端股骨小梁骨图像自动配准的可行性,以及灰度插值和感兴趣体积(VOI)未对准对MR衍生的小梁骨结构参数的影响。在一项短期研究中,对6名受试者在同一天获取了近端股骨的基线扫描和随访扫描。在一项长期研究中,对10名受试者在基线扫描1年后获取了近端股骨的随访扫描。一种基于互信息的自动图像配准技术利用基线扫描和随访扫描来计算使两幅图像对齐的变换参数。在短期研究中,随后使用这些参数用三种不同的灰度插值器对随访图像进行变换。最近邻插值和B样条逼近对骨参数没有显著改变,而线性插值显著改变了骨参数(p<0.01)。通过检查差异图像和三维渲染图来确定长期和短期研究中自动配准带来的图像对齐改善情况。这项工作展示了在未进行预先分割的情况下,首次将自动配准应用于近端股骨高空间分辨率小梁骨MR图像。此外,小梁骨结构固有的异质性以及VOI在切片(前后)方向上的定位不精确导致骨参数发生显著变化(p<0.01)。结果表明,使用B样条逼近或最近邻灰度插值进行自动互信息配准以变换最终图像,可确保基线图像和随访图像之间的VOI对齐,且不会损害本研究中使用的MR衍生小梁骨参数的完整性。

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IEEE Trans Med Imaging. 1983;2(1):31-9. doi: 10.1109/TMI.1983.4307610.

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