title: Track orientation density imaging (TODI) and track orientation distribution (TOD) based tractography.
abstract: Ever since the introduction of the concept of fiber tractography, methods to generate better and more plausible tractograms have become available. Many modern methods can handle complex fiber architecture and take on a probabilistic approach to account for different sources of uncertainty. The resulting tractogram from any such method typically represents a finite random sample from a complex distribution of possible tracks. Generating a higher amount of tracks allows for a more accurate depiction of the underlying distribution. The recently proposed method of track-density imaging (TDI) allows to capture the spatial distribution of a tractogram. In this work, we propose an extension of TDI towards the 5D spatio-angular domain, which we name track orientation density imaging (TODI). The proposed method aims to capture the full track orientation distribution (TOD). Just as the TDI map, the TOD is amenable to spatial super-resolution (or even sub-resolution), but in addition also to angular super-resolution. Through experiments on in vivo human subject data, an in silico numerical phantom and a challenging tractography phantom, we found that the TOD presents an increased amount of regional spatio-angular consistency, as compared to the fiber orientation distribution (FOD) from constrained spherical deconvolution (CSD). Furthermore, we explain how the amplitude of the TOD of a short-tracks distribution (i.e. where the track length is limited) can be interpreted as a measure of track-like local support (TLS). This in turn motivated us to explore the idea of TOD-based fiber tractography. In such a setting, the short-tracks TOD is able to guide a track along directions that are more likely to correspond to continuous structure over a longer distance. This powerful concept is shown to greatly robustify targeted as well as whole-brain tractography. We conclude that the TOD is a versatile tool that can be cast in many different roles and scenarios in the expanding domain of fiber tractography based methods and their applications.
authors.affiliation: Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium; Medical Image Computing (MIC), ESAT-PSI, Department of Electrical Engineering, KU Leuven, Leuven, Belgium. Electronic address: thijs.dhollander@gmail.com.
authors.forename: Thijs
authors.initials: T
authors.lastname: Dhollander
authors.affiliation: Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium; Translational MRI, Department of Imaging & Pathology, KU Leuven, Leuven, Belgium; Department of Radiology, UZ Leuven, Leuven, Belgium; Leuven Research Institute for Neuroscience & Disease (LIND), KU Leuven, Leuven, Belgium.
authors.forename: Louise
authors.initials: L
authors.lastname: Emsell
authors.affiliation: Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium.
authors.forename: Wim
authors.initials: W
authors.lastname: Van Hecke
authors.affiliation: Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium; Medical Image Computing (MIC), ESAT-PSI, Department of Electrical Engineering, KU Leuven, Leuven, Belgium.
authors.forename: Frederik
authors.initials: F
authors.lastname: Maes
authors.affiliation: Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium; Translational MRI, Department of Imaging & Pathology, KU Leuven, Leuven, Belgium; Department of Radiology, UZ Leuven, Leuven, Belgium; Leuven Research Institute for Neuroscience & Disease (LIND), KU Leuven, Leuven, Belgium.
authors.forename: Stefan
authors.initials: S
authors.lastname: Sunaert
authors.affiliation: Medical Imaging Research Center (MIRC), KU Leuven, Leuven, Belgium; Medical Image Computing (MIC), ESAT-PSI, Department of Electrical Engineering, KU Leuven, Leuven, Belgium; iMinds - KU Leuven Future Health Department, Leuven, Belgium.
authors.forename: Paul
authors.initials: P
authors.lastname: Suetens
mesh_terms: D000465:Algorithms; D001921:Brain / Q000166:cytology*; D003198:Computer Simulation; D056324:Diffusion Tensor Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D015233:Models, Statistical; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D010363:Pattern Recognition, Automated / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique
keywords: Diffusion weighted imaging; Fiber orientation distribution; Fiber tractography; Track orientation density imaging; Track orientation distribution; Track orientation weighted imaging; Track-density imaging; Track-like local support; Track-weighted imaging