Non-linear integration of DTI-based fiber tracts into standard 3D MR data

Abstract

Diffusion tensor imaging (DTI) provides information about the location of white matter tracts within the human brain. This information is essential for preoperative neurosurgical planning to achieve maximal tumor resection while avoiding postoperative neurological deficits. Due to the anatomical distortion of echo planar imaging, DT images- and as a result the fiber tracts computed from them-are distorted. In this paper, we present a novel approach to account for those distortions. All voxels containing fibers within the distorted DT dataset were marked. Subsequently, a non-linear registration with standard 3D MR data was performed. The marked voxels were re-extracted from the registered DT dataset and displayed within the 3D MR dataset. The strategy introduced in this paper is an essential prerequisite for the integration of fiber tract data into 3D MR datasets. The fused data is of high value for neuronavigation and thereby a benefit for neurosurgery.

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