Flow-Based Fiber Tracking With Diffusion Tensor and Q-Ball Data:

this paper, we extend our previously proposed flow-based fiber tracking approaches (Campbell et al., 2002a,b) in order to use the information in the full diffusion pdf estimated using either HARD or DT techniques. This algorithm is a modification and extension of the Fast Marching Tractography (FMT) technique (Parker et al., 2002a), which uses the principal diffusion direction only, and is similar to several surface evolution approaches that use the full diffusion tensor (Batchelor et al., 2001; O'Donnell et al., 2002; Tournier et al., 2003). Our extension of the FMT technique consists of using all of the information in the diffusion tensor or, if available, HARD measurements. The surface evolution approach has the advantage that it allows tracking to proceed in a continuum of directions, as may be desired in cases where there is uncertainty and/or multiple fiber directions. We show fiber tracking results using both HARD and DT data in the human brain, noting that the diffusion tensor can provide more information than that given by its principal eigenvector only and that HARD reconstruction can give us more information still. Additionally, we quantitatively compare the performance of the flow-based approach to that of line propagation using the PDD. To do so, we designed a physical phantom with known connectivity from excised rat spinal cord. Previous validation studies have been done using a single excised cord (Campbell et al., 2002b; Vemuri et al., 2002) and in the macaque (Parker et al., 2002b): in this study, complex known configurations of subvoxel curvature and fiber crossing are created and scanned at a standard human imaging resolution. While simulated data can provide a gold standard to which tracking results can be compared (Lazar and Alexander, 2003; Lori et..