Thijs Dhollander1,2, Wim Van Hecke1,3,
Frederik Maes1,2, Stefan Sunaert1,3, Paul Suetens,,2
1Medical Imaging Research
Center (MIRC), K.U.Leuven, Leuven, Belgium; 2Department of
Electrical Engineering (ESAT), K.U.Leuven, Leuven, Belgium; 3Department
of Radiology, University Hospitals of the K.U.Leuven, Leuven, Belgium
In the context of registration algorithms, the application of spatial transformations to images is crucial. This poses a challenge of its own for diffusion weighted imaging (DWI) data, since the information in every voxel is dependent on the angular structure of the underlying tissue. After interpolation, an extra reorientation step to correct the data in each voxel is necessary. We review different reorientation strategies, starting from the basic methods that operate on the tensor from diffusion tensor imaging (DTI) and building up to full fiber orientation distribution function (fODF) retransformation and methods that work on the raw data in q-space.
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