Spatial transformations of diffusion tensor magnetic resonance images

We address the problem of applying spatial transformations (or "image warps ") to diffusion tensor magnetic resonance images. The orientational informa tion that these images contain must be handled appropriately when they are transformed spatially during image registration. We present solutions for g lobal transformations of three-dimensional images up to 12-parameter affine complexity and indicate how our methods can be extended for higher order t ransformations. Several approaches are presented and tested using synthetic data. One method, the preservation of principal direction algorithm, which takes into account shearing, stretching and rigid rotation, is shown to be the most effective. Additional registration experiments are performed on h uman brain data obtained from a single subject, whose head was imaged in th ree different orientations within the scanner. All of our methods improve t he consistency between registered and target images over naive warping algo rithms.