A Novel Interface for Interactive Exploration of DTI Fibers

Abstract

Abstract-Visual exploration is essential to the visualization and analysis of densely sampled 3D DTI fibers in biological speciments, due to the high geometric, spatial, and anatomical complexity of fiber tracts. Previous methods for DTI fiber visualization use zooming, color-mapping, selection, and abstraction to deliver the characteristics of the fibers. However, these schemes mainly focus on the optimization of visualization in the 3D space where cluttering and occlusion make grasping even a few thousand fibers difficult. This paper introduces a novel interaction method that augments the 3D visualization with a 2D representation containing a low-dimensional embedding of the DTI fibers. This embedding preserves the relationship between the fibers and removes the visual clutter that is inherent in 3D renderings of the fibers. This new interface allows the user to manipulate the DTI fibers as both 3D curves and 2D embedded points and easily compare or validate his or her results in both domains. The implementation of the framework is GPUbased to achieve real-time interaction. The framework was applied to several tasks, and the results show that our method reduces the user's workload in recognizing 3D DTI fibers and permits quick and accurate DTI fiber selection.

DTI tractography and white matter fiber tract characteristics in euthymic bipolar I patients and healthy control subjects

“…While FA is among the most commonly found metrics of white matter structure in DTI studies, Koraonkar and coworkers (Korgaonkar, Cooper et al 2012) found through independent components analysis that fiber length has a predictive accuracy of 83% when measured in major depressive disorder vs. control subjects. Furthermore, because of its crucial role in fiber-tracking algorithms and its correlation to other metrics, fiber length is considered a valuable metric for assessing the accuracy of tractography protocols (Andreisek, White et al 2009; Chen, Ding et al 2009; Colby, Soderberg et al 2012; Kristo, Leemans et al 2012). Moreover, our use of multivariate analysis was conducted in order to specifically account for such covariance and improve on the ability to detect differences between groups.…”

Pondering the Concept of Abstraction in (Illustrative) Visualization

“…Other examples for geometric abstractions are subway networks ( Fig. 1) and the contraction-based abstraction of brain connectivity [21], [22], [32] (Fig. 7).…”

“…Visual abstraction operators, on the other hand, strongly rely on cognition and need to be learned, similar to arbitrary symbols. 21 In addition to this connection to cognition and perception, several additional links to other fields that discuss abstraction can be made. Refinement in computing, for instance, is a concept that uses a verifiable transformation from an abstract program specification to a specific form that can then be executed.…”

Accelerating Fibre Orientation Estimation from Diffusion Weighted Magnetic Resonance Imaging Using GPUs

“…However, in [47], [48] GPUs were used only for visualising tractography results. The approaches proposed in [49]–[51] perform deterministic tractography rather than dealing with a probabilistic Bayesian inference framework, as in our study.…”