首页> 外文期刊>Journal of magnetic resonance imaging: JMRI >Retrospective 3D registration of trabecular bone MR images for longitudinal studies.
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Retrospective 3D registration of trabecular bone MR images for longitudinal studies.

机译:小梁骨MR图像的回顾性3D配准用于纵向研究。

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PURPOSE: To evaluate an automatic 3D registration algorithm for serial high-resolution images of trabecular bone (TB) in studies designed to evaluate the response of the trabecular architecture to intervention or disease progression. MATERIALS AND METHODS: An efficient algorithm for registering high-resolution 3D images of TB is presented. The procedure identifies the six parameters of rigid displacement between two scans performed at different timepoints. By assuming a relatively small through-plane rotation, considerable time is saved by combining the results of a collection of regional 2D registrations throughout the TB region of interest (ROI). The algorithm was applied to 26 pairs of MR images acquired 6 months apart. Reproducibility of local TB structural parameters (plate, rod, and junction density) computed in manually selected regions were compared between baseline and registered follow-up images. RESULTS: All 26 registrations were completed successfully in less than 30 seconds per image pair.The resampled follow-up images agreed with baseline to around one pixel throughout the volume at 137 x 137 x 410 microm(3) image resolution. Structural parameters in each region correlated well from baseline to follow-up with intraclass correlation coefficients ranging between 85%-97% for TB plate density. Interregional variations in the parameters were large as compared with intraregion reproducibility. CONCLUSION: The proposed algorithm was successful in automatically registering baseline and follow-up TB images in a translational study, and may be useful in regional analyses in longitudinal MR studies of TB architecture.
机译:目的:在旨在评估骨小梁结构对干预或疾病进展的反应的研究中,评估小梁骨(TB)系列高分辨率图像的自动3D注册算法。材料与方法:提出了一种用于记录结核的高分辨率3D图像的有效算法。该过程确定了在不同时间点进行的两次扫描之间的刚性位移的六个参数。通过假设相对较小的直通平面旋转,通过组合整个感兴趣的TB区域(ROI)的区域2D配准的结果,可以节省大量时间。该算法应用于间隔6个月获取的26对MR图像。在基线和注册的随访图像之间比较了在手动选择的区域中计算出的局部结核病结构参数(板,杆和结密度)的可重复性。结果:每对图像在不到30秒的时间内成功完成了全部26个配准。重新采样的后续图像与基线一致,整个像素的分辨率约为137 x 137 x 410 microm(3)。从基线到随访,每个区域的结构参数均具有良好的相关性,对于结核病菌密度,组内相关系数在85%-97%之间。与区域内的可重复性相比,区域间的参数差异较大。结论:所提出的算法在翻译研究中成功地自动注册了基线和后续的结核病图像,可能对结核病建筑纵向MR研究中的区域分析有用。

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