Breighner Ryan, Holmes David R, Leng Shuai, An Kai-Nan, McCollough Cynthia, Zhao Kristin
Biomechanics Laboratory, Division of Orthopedic Research.
Biomedical Imaging Resource, Mayo Clinic, 200 First Street SW, Rochester, MN 55905.
Proc SPIE Int Soc Opt Eng. 2013 Feb 9;8671. doi: 10.1117/12.2008685. Epub 2013 Mar 12.
It is often necessary to register partial objects in medical imaging. Due to limited FOV, the entirety of an object cannot always be imaged. This study presents a novel application of an existing registration algorithm to this problem. The spin-image algorithm [1] creates pose-invariant representations of global shape with respect to individual mesh vertices. These 'spin-images,' are then compared for two different poses of the same object to establish correspondences and subsequently determine relative orientation of the poses. In this study, the spin-image algorithm is applied to 4DCT-derived capitate bone surfaces to assess the relative accuracy of registration with various amounts of geometry excluded. The limited longitudinal coverage under the 4DCT technique (38.4mm, [2]), results in partial views of the capitate when imaging wrist motions. This study assesses the ability of the spin-image algorithm to register partial bone surfaces by artificially restricting the capitate geometry available for registration. Under IRB approval, standard static CT and 4DCT scans were obtained on a patient. The capitate was segmented from the static CT and one phase of 4DCT in which the whole bone was available. Spin-image registration was performed between the static and 4DCT. Distal portions of the 4DCT capitate (10-70%) were then removed and registration was repeated. Registration accuracy was evaluated by angular errors and the percentage of sub-resolution fitting. It was determined that 60% of the distal capitate could be omitted without appreciable effect on registration accuracy using the spin-image algorithm (angular error < 1.5 degree, sub-resolution fitting > 98.4%).
在医学成像中，常常需要对部分对象进行配准。由于视野有限，无法总是对整个对象进行成像。本研究提出了一种将现有配准算法应用于该问题的新方法。自旋图像算法[1]针对单个网格顶点创建全局形状的姿态不变表示。然后，针对同一对象的两种不同姿态比较这些“自旋图像”，以建立对应关系并随后确定姿态的相对方向。在本研究中，自旋图像算法应用于从4DCT得出的头状骨表面，以评估在排除不同几何量的情况下配准的相对准确性。4DCT技术下有限的纵向覆盖范围（38.4毫米，[2]），导致在对腕部运动进行成像时只能获得头状骨的部分视图。本研究通过人为限制可用于配准的头状骨几何形状，评估自旋图像算法对部分骨表面进行配准的能力。在获得机构审查委员会批准后，对一名患者进行了标准静态CT和4DCT扫描。从头状骨的静态CT和4DCT的一个整个骨骼可用的阶段中分割出头状骨。在静态CT和4DCT之间进行自旋图像配准。然后去除4DCT头状骨的远端部分（10 - 70%）并重复配准。通过角度误差和亚分辨率拟合百分比评估配准准确性。结果确定，使用自旋图像算法时，头状骨远端的60%可以省略而对配准准确性没有明显影响（角度误差<1.5度，亚分辨率拟合>98.4%）。
