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Interactive visualization of volumetric white matter connectivity in DT-MRI using a parallel-hardware Hamilton-Jacobi solver.
IEEE Trans Vis Comput Graph. 2007 Nov-Dec; 13(6):1480-7.IT

Abstract

In this paper we present a method to compute and visualize volumetric white matter connectivity in diffusion tensor magnetic resonance imaging (DT-MRI) using a Hamilton-Jacobi (H-J) solver on the GPU (Graphics Processing Unit). Paths through the volume are assigned costs that are lower if they are consistent with the preferred diffusion directions. The proposed method finds a set of voxels in the DTI volume that contain paths between two regions whose costs are within a threshold of the optimal path. The result is a volumetric optimal path analysis, which is driven by clinical and scientific questions relating to the connectivity between various known anatomical regions of the brain. To solve the minimal path problem quickly, we introduce a novel numerical algorithm for solving H-J equations, which we call the Fast Iterative Method (FIM). This algorithm is well-adapted to parallel architectures, and we present a GPU-based implementation, which runs roughly 50-100 times faster than traditional CPU-based solvers for anisotropic H-J equations. The proposed system allows users to freely change the endpoints of interesting pathways and to visualize the optimal volumetric path between them at an interactive rate. We demonstrate the proposed method on some synthetic and real DT-MRI datasets and compare the performance with existing methods.

Authors+Show Affiliations

Jeong WK
Scientific Computing and Imaging Instiutte, School of Computing, University of Utah, Salt Lake City 84112, USA. wkjeong@sci.utah.edu
Fletcher PT
No affiliation info available
Tao R
No affiliation info available
Whitaker R
No affiliation info available

MeSH

AlgorithmsBrainComputer GraphicsComputer SimulationDiffusion Magnetic Resonance ImagingEquipment DesignEquipment Failure AnalysisHumansImage EnhancementImage Interpretation, Computer-AssistedModels, BiologicalModels, StatisticalNerve Fibers, MyelinatedNeural PathwaysNumerical Analysis, Computer-AssistedReproducibility of ResultsSensitivity and SpecificitySignal Processing, Computer-AssistedUser-Computer Interface

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

17968100

Citation

Jeong, Won-Ki, et al. "Interactive Visualization of Volumetric White Matter Connectivity in DT-MRI Using a Parallel-hardware Hamilton-Jacobi Solver." IEEE Transactions On Visualization and Computer Graphics, vol. 13, no. 6, 2007, pp. 1480-7.
Jeong WK, Fletcher PT, Tao R, et al. Interactive visualization of volumetric white matter connectivity in DT-MRI using a parallel-hardware Hamilton-Jacobi solver. IEEE Trans Vis Comput Graph. 2007;13(6):1480-7.
Jeong, W. K., Fletcher, P. T., Tao, R., & Whitaker, R. (2007). Interactive visualization of volumetric white matter connectivity in DT-MRI using a parallel-hardware Hamilton-Jacobi solver. IEEE Transactions On Visualization and Computer Graphics, 13(6), 1480-7.
Jeong WK, et al. Interactive Visualization of Volumetric White Matter Connectivity in DT-MRI Using a Parallel-hardware Hamilton-Jacobi Solver. IEEE Trans Vis Comput Graph. 2007 Nov-Dec;13(6):1480-7. PubMed PMID: 17968100.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Interactive visualization of volumetric white matter connectivity in DT-MRI using a parallel-hardware Hamilton-Jacobi solver. AU - Jeong,Won-Ki, AU - Fletcher,P Thomas, AU - Tao,Ran, AU - Whitaker,Ross, PY - 2007/10/31/pubmed PY - 2007/12/15/medline PY - 2007/10/31/entrez SP - 1480 EP - 7 JF - IEEE transactions on visualization and computer graphics JO - IEEE Trans Vis Comput Graph VL - 13 IS - 6 N2 - In this paper we present a method to compute and visualize volumetric white matter connectivity in diffusion tensor magnetic resonance imaging (DT-MRI) using a Hamilton-Jacobi (H-J) solver on the GPU (Graphics Processing Unit). Paths through the volume are assigned costs that are lower if they are consistent with the preferred diffusion directions. The proposed method finds a set of voxels in the DTI volume that contain paths between two regions whose costs are within a threshold of the optimal path. The result is a volumetric optimal path analysis, which is driven by clinical and scientific questions relating to the connectivity between various known anatomical regions of the brain. To solve the minimal path problem quickly, we introduce a novel numerical algorithm for solving H-J equations, which we call the Fast Iterative Method (FIM). This algorithm is well-adapted to parallel architectures, and we present a GPU-based implementation, which runs roughly 50-100 times faster than traditional CPU-based solvers for anisotropic H-J equations. The proposed system allows users to freely change the endpoints of interesting pathways and to visualize the optimal volumetric path between them at an interactive rate. We demonstrate the proposed method on some synthetic and real DT-MRI datasets and compare the performance with existing methods. SN - 1077-2626 UR - https://www.unboundmedicine.com/medline/citation/17968100/Interactive_visualization_of_volumetric_white_matter_connectivity_in_DT_MRI_using_a_parallel_hardware_Hamilton_Jacobi_solver_ DB - PRIME DP - Unbound Medicine ER -