Department of Biomedical Engineering, School of Life Sciences & Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China; E-Mail:
Sensors (Basel). 2009;9(12):10270-90. doi: 10.3390/s91210270. Epub 2009 Dec 17.
This paper proposes a novel global-to-local nonrigid brain MR image registration to compensate for the brain shift and the unmatchable outliers caused by the tumor resection. The mutual information between the corresponding salient structures, which are enhanced by the joint saliency map (JSM), is maximized to achieve a global rigid registration of the two images. Being detected and clustered at the paired contiguous matching areas in the globally registered images, the paired pools of DoG keypoints in combination with the JSM provide a useful cluster-to-cluster correspondence to guide the local control-point correspondence detection and the outlier keypoint rejection. Lastly, a quasi-inverse consistent deformation is smoothly approximated to locally register brain images through the mapping the clustered control points by compact support radial basis functions. The 2D implementation of the method can model the brain shift in brain tumor resection MR images, though the theory holds for the 3D case.
本文提出了一种新颖的全局到局部的非刚性脑磁共振图像配准方法，以补偿由于肿瘤切除引起的脑移位和不匹配的离群点。通过联合显著图（JSM）增强对应的显著结构之间的互信息，实现了两幅图像的全局刚性配准。在全局配准图像的配对连续匹配区域中进行检测和聚类，结合 JSM 的成对 DOG 关键点池提供了有用的聚类到聚类对应关系，以指导局部控制点对应关系检测和异常关键点剔除。最后，通过紧凑支持径向基函数映射聚类控制点，对局部配准脑图像进行平滑逼近拟合成准逆一致变形。该方法的 2D 实现可以模拟脑肿瘤切除磁共振图像中的脑移位，尽管该理论适用于 3D 情况。
