Deformable Registration of Diffusion Tensor MR Images with Explicit Orientation Optimization

In this paper, we present a novel deformable registration algorithm for diffusion tensor MR images that enables explicit optimization of tensor reorientation. The optimization seeks a piecewise affine transformation that divides the image domain into uniform regions and transform each region affinely. The objective function captures both the image similarity and the smoothness of the transformation across region boundaries. The image similarity enables explicit orientation optimization by incorporating tensor reorientation, which is necessary for warping diffusion tensor images. The objective function is formulated in a way that allows explicit implementation of analytic derivatives to drive fast and accurate optimization using the conjugate gradient method. By explicitly optimizing tensor reorientation, the algorithm is designed to take advantage of similarity measures comparing tensors as a whole. The optimal transformation is hierarchically refined in a subdivision framework. A com...

• Type: Conference
• Year: 2005
• Where: MICCAI
• Authors: Hui Zhang 0005, Paul A. Yushkevich, James C. Gee
• Keywords: Diffusion Tensor Images, Diffusion Tensor MR, Medical Imaging, MICCAI 2005, Tensor Reorientation