Geometric distortion correction of high-resolution 3 T diffusion tensor brain images

Diffusion-weighted images based on echo planar sequences suffer from distortions due to field inhomogeneities from susceptibility differences as well as from eddy currents arising from diffusion gradients. In this paper, a novel approach using nonlinear warping based on optic flow to correct distortions of baseline and diffusion weighted echo planar images (EPI) acquired at 3 T is presented. The distortion correction was estimated by warping the echo planar images to the anatomically correct T₂-weighted fast spin echo images (T2-FSE). A global histogram intensity matching of the T2-FSE precedes the base line EPI image distortion correction. A local intensity-matching algorithm was used to transform labeled T2-FSE regions to match intensities of diffusion-weighted EPI images prior to distortion correction of these images. Evaluation was performed using three methods: (i) visual comparison of overlaid contours, (ii) a global mutual information index, and (iii) a local distance measure between homologous points. Visual assessment and the global index demonstrated a decrease in geometrical distortion and the distance measure showed that distortions are reduced to a subvoxel level. In conclusion, the warping algorithm is effective in reducing geometric distortions, enabling generation of anatomically correct diffusion tensor images at 3 T.