Boundary-based warping of brain MR images

The goal of this work was to develop a warping technique for mapping a brai n image to another image or atlas data, with minimum user interaction and i ndependent of gray level information. We have developed and tested three di fferent methods for warping magnetic resonance (MR) brain Images. We utiliz e a deformable contour to extract and warp the boundaries of the two images . A mesh-grid coordinate system Is constructed for each brain, by applying a distance transformation to the resulting contours, and scaling. In the fi rst method (MGC), the first Image is mapped to the second Image based on a one-to-one mapping between different layers defined by the mesh-grid. In th e second method (IDW), the corresponding pixels in the two images are found using the above mesh-grid system and a local Inverse-distance weights inte rpolation. In the third proposed method (TSB), a subset of grid points Is u sed for finding the parameters of a spline transformation, which defines th e global warping. The warping methods were applied to clinical MR consistin g of diffusion-weighted and T2-weighted images of the human brain. The IDW and TSB methods were superior in ranking of diagnostic quality of the warpe d MR images to the MGC (P < 0.01) as defined by a neuroradiologist. The def ormable contour warping produced excellent diagnostic quality for the diffu sion-weighted images coregistered and warped to T2 weighted images. (C) 200 0 Wiley-Liss, Inc.