Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
Digital Image Processing
IEEE Computer Graphics and Applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
3D brain surface matching based on geodesics and local geometry
Computer Vision and Image Understanding - Special issue on nonrigid image registration
Hybrid Image Registration based on Configural Matching of Scale-Invariant Salient Region Features
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 11 - Volume 11
Efficient partial-surface registration for 3D objects
Computer Vision and Image Understanding
Monomodal image registration using mutual information based methods
Image and Vision Computing
Computers in Biology and Medicine
Likelihood maximization approach to image registration
IEEE Transactions on Image Processing
Computer Methods and Programs in Biomedicine
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A robust and fast hybrid method using a shell volume that consists of high contrast voxels with their neighbors is proposed for registering PET and MR/CT brain images. Whereas conventional hybrid methods find the best matched pairs from several manually selected or automatically extracted local regions, our method automatically selects a shell volume in the PET image, and finds the best matched corresponding volume using normalized mutual information (NMI) in overlapping volumes while transforming the shell volume into an MR or CT image. A shell volume not only can reduce irrelevant corresponding voxels between two images during optimization of transformation parameters, but also brings a more robust registration with less computational cost. Experimental results on clinical data sets showed that our method successfully aligned all PET and MR/CT image pairs without losing any diagnostic information, while the conventional registration methods failed in some cases.