title: Susceptibility distortion correction for echo planar images with non-uniform B-spline grid sampling: a diffusion tensor image study.
abstract: In this paper, we propose a novel method for correcting the geometric distortions in diffusion weighted images (DWI) obtained with echo planar imaging (EPI) protocol. Our EPI distortion correction approach employs a deformable registration framework with the B-splines transformation, where the control point distributions are non-uniform and functions of the expected norm of the spatial distortions. In our framework, the amount of distortions are first computed by estimating the B(0) fieldmap from an initial segmentation of a distortion-free structural image and tissue susceptibility models. Fieldmap estimates are propagated to obtain expected spatial distortion maps, which are used in the sampling of active B-spline control points. This transformation is flexible in locations with large distortion expectations, yet with relatively few degrees-of-freedom and does not suffer from local optima convergence and hence does not distort anatomically salient locations. Results indicate that with the proposed correction scheme, tensor derived scalar maps and fiber tracts of the same subject computed from data acquired with different phase encoding directions provide better coherency and consistency compared traditional registration based approaches.
authors: Computer Sciences and Engineering Department, The Ohio State University, USA. irfanoglu.1@osu.edu
authors: M O
authors: MO
authors: Irfanoglu
authors: L
authors: L
authors: Walker
authors: S
authors: S
authors: Sammet
authors: C
authors: C
authors: Pierpaoli
authors: R
authors: R
authors: Machiraju
mesh_terms: D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000473:pathology; D001931:Brain Mapping / Q000379:methods; D003201:Computers; D056324:Diffusion Tensor Imaging / Q000379:methods*; D004548:Elasticity; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D015233:Models, Statistical