Hemler P F, Napel S, Sumanaweera T S, Pichumani R, van den Elsen P A, Martin D, Drace J, Adler J R, Perkash I
Stanford University Medical Center, Stanford University, California, USA.
Med Phys. 1995 Jul;22(7):1049-56. doi: 10.1118/1.597591.
This paper presents a new reference data set and associated quantification methodology to assess the accuracy of registration of computerized tomography (CT) and magnetic-resonance (MR) images. Also described is a new semiautomatic surface-based system for registering and visualizing CT and MR images. The registration error of the system was determined using a reference data set that was obtained from a cadaver in which rigid fiducial tubes were inserted prior to imaging. Registration error was measured as the distance between an analytic expression for each fiducial tube in one image set and transformed samples of the corresponding tube obtained from the other. Registration was accomplished by first identifying surfaces of similar anatomic structures in each image set. A transformation that best registered these structures was determined using a nonlinear optimization procedure. Even though the root-mean-square (rms) distance at the registered surfaces was similar to that reported by other groups, it was found that rms distances for the tubes were significantly larger than the final rms distances between the registered surfaces. It was also found that minimizing rms distance at the surface did not minimize rms distance for the tubes.
本文提出了一种新的参考数据集及相关量化方法，用于评估计算机断层扫描（CT）和磁共振（MR）图像配准的准确性。还介绍了一种用于配准和可视化CT与MR图像的新型半自动基于表面的系统。该系统的配准误差是使用从一具尸体获取的参考数据集来确定的，该尸体在成像前已插入刚性基准管。配准误差被测量为一个图像集中每个基准管的解析表达式与从另一个图像集获得的相应管的变换样本之间的距离。配准首先通过识别每个图像集中相似解剖结构的表面来完成。使用非线性优化程序确定能最佳配准这些结构的变换。尽管配准表面处的均方根（rms）距离与其他研究小组报告的相似，但发现基准管的rms距离明显大于配准表面之间的最终rms距离。还发现，使表面处的rms距离最小化并不会使基准管的rms距离最小化。
