Takao Masaki, Sugano Nobuhiko, Nishii Takashi, Miki Hidenobu, Koyama Tsuyoshi, Masumoto Jun, Sato Yoshinobu, Tamura Shinichi, Yoshikawa Hideki
Department of Orthopedic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan.
J Magn Reson Imaging. 2005 Nov;22(5):656-60. doi: 10.1002/jmri.20435.
To estimate the accuracy and consistency of a method using a voxel-based MR image registration algorithm for precise monitoring of knee joint diseases.
Rigid body transformation was calculated using a normalized cross-correlation (NCC) algorithm involving simple manual segmentation of the bone region based on its anatomical features. The accuracy of registration was evaluated using four phantoms, followed by a consistency test using MR data from the 11 patients with knee joint disease.
The registration accuracy in the phantom experiment was 0.49+/-0.19 mm (SD) for the femur and 0.56+/-0.21 mm (SD) for the tibia. The consistency value in the experiment using clinical data was 0.69+/-0.25 mm (SD) for the femur and 0.77+/-0.37 mm (SD) for the tibia. These values were all smaller than a voxel (1.25 x 1.25 x 1.5 mm).
The present method based on an NCC algorithm can be used to register serial MR images of the knee joint with error on the order of a sub-voxel. This method would be useful for precisely assessing therapeutic response and monitoring knee joint diseases; normalized cross-correlation; accuracy.
评估一种基于体素的磁共振图像配准算法用于精确监测膝关节疾病的方法的准确性和一致性。
采用归一化互相关(NCC)算法计算刚体变换,该算法基于骨骼区域的解剖特征进行简单的手动分割。使用四个模型评估配准的准确性,随后使用11例膝关节疾病患者的磁共振数据进行一致性测试。
模型实验中股骨的配准精度为0.49±0.19毫米(标准差),胫骨为0.56±0.21毫米(标准差)。使用临床数据的实验中股骨的一致性值为0.69±0.25毫米(标准差),胫骨为0.77±0.37毫米(标准差)。这些值均小于一个体素(1.25×1.25×1.5毫米)。
基于NCC算法的本方法可用于配准膝关节的系列磁共振图像,误差在亚体素量级。该方法对于精确评估治疗反应和监测膝关节疾病将是有用的;归一化互相关;准确性。