Abstract
Fiber tracking is a technique that, based on a diffusion tensor magnetic resonance imaging dataset, locates the fiber bundles in the human brain. Because it is a computationally expensive process, the interactivity of current fiber tracking tools is limited. We propose a new approach, which we termed real-time interactive fiber tracking, which aims at providing a rich and intuitive environment for the neuroradiologist. In this approach, fiber tracking is executed automatically every time the user acts upon the application. Particularly, when the volume of interest from which fiber trajectories are calculated is moved on the screen, fiber tracking is executed, even while it is being moved. We present our fiber tracking tool, which implements the real-time fiber tracking concept by using the video card’s graphics processing units to execute the fiber tracking algorithm. Results show that real-time interactive fiber tracking is feasible on computers equipped with common, low-cost video cards.
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Basser PJ, Mattiello J, Le Bihan D: MR diffusion tensor spectroscopy and imaging. Biophys J 66:259–267, 1994
Basser PJ, Mattiello J, Le Bihan, D: Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 103:247–254, 1994.
Le Bihan D, Mangin JF, Poupon C, Clark CA, Pappata S, Molko N, Chabriat H: Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging 13:534–546, 2001.
Yamada K, Shiga K, Kizu O, Ito H, Akiyama K, Nakagawa M, Nishimura T: Oculomotor nerve palsy evaluated by diffusion-tensor tractography. Neuroradiology 48:434–437, 2006.
Beaulieu C: The basis of anisotropic water diffusion in the nervous system—a technical review. NMR Biomed, 15:435–455, 2002.
Conturo TE, Lori NF, Cull TS, Akbudak E, Snyder AZ, Shimony JS, McKinstry RC, Burton H, Raichle ME: Tracking neuronal fiber pathways in the living human brain. Proc. Natl. Acad. Sci. USA 96, 10422–10427, 1999.
Basser PJ, Pajevic S, Pierpaoli C, Aldroubi A: Fiber tract following in the human brain using DT-MRI data. IEICE Trans Inf & Syst E85-D:15–21, 2002.
Hagmann P, Jonasson L, Deffieux T, Meuli R, Thiran J, Wedeen VJ: Fibertract segmentation in position orientation space from high angular resolution diffusion MRI. NeuroImage 32:665–675, 2006.
Friman O, Farnebäck G, Westin C: A Bayesian approach for stochastic white matter tractography. IEEE Trans Med Imaging 25:965–978, 2006.
Staempfli P, Jaermann T, Crelier GR, Kollias S, Valavanis A, Boesiger P: Resolving fiber crossing using advanced fast marching tractography based on diffusion tensor imaging. NeuroImage 30:110–120, 2006.
Mori S, van Zijl PCM: Fiber tracking: principles and strategies—a technical review. NMR Biomed 15:468–480, 2002.
Dellani PR, Glaser M, Wille PR, Vucurevic G, Stadie A, Bauermann T, Tropine A, Perneczky A, von Wangenheim, A, Stoeter P: White matter fiber tracking computation based on diffusion tensor imaging for clinical applications. J Digit Imaging 20:88–97, 2007.
Pajevic S, Aldroubi A, Basser PJ: A continuous tensor field approximation of discrete DT-MRI data for extracting microstructural and architectural features of tissue. J Magn Reson 154:85–100, 2002.
BrainLAB. iPlan BOLD MRI Mapping. Available at http://www.brainlab.com/. Visited on 18 March 2009.
Brain Innovation B.V. BrainVoyager QX. Available at http://www.brainvoyager.com/. Visited on 18 March 2009.
Goebel R, Esposito F, Formisano E: Analysis of functional image analysis contest (FIAC) data with Brainvoyager QX: From single-subject to cortically aligned group general linear model analysis and self-organizing group independent component analysis. Human Brain Mapping 27:392–401, 2001.
Roebroeck A, Galuske R, Formisano E, Chiry O, Bratzke H, Ronen I, Kim DS, Goebel R: High-resolution diffusion tensor imaging and tractography of the human optic chiasm at 9.4 T. NeuroImage 39:157–186, 2008.
Jeong W, Fletcher P, Tao R, Whitaker R: Interactive Visualization of Volumetric White Matter Connectivity in DT-MRI Using a Parallel-Hardware Hamilton-Jacobi Solver. IEEE Trans Vis Comp Graph 13:1480–1487, 2007.
Petrovic V, Fallon J, Kuester F: Visualizing Whole-Brain DTI Tractography with GPU-based Tuboids and LoD Management. IEEE Trans Vis Comp Graph 13:1488–1495, 2007.
McGraw T, Nadar M: Stochastic DT-MRI Connectivity Mapping on the GPU. IEEE Trans Vis Comp Graph. 13:1504–1511, 2007.
Mittmann A, Comunello E, von Wangenheim A: Diffusion tensor fiber tracking on graphics processing units. Comput Med Imaging Graph 32:521–530, 2008.
Mittmann A, Dantas MAR, von Wangenheim A: Design and Implementation of Brain Fiber Tracking for GPUs and PC Clusters. Proc. 21st International Symposium on Computer Architecture and High Performance Computing SBAC-PAD, São Paulo, 101–108, 2009.
Köhn A, Klein J, Weiler F, Peitgen H-O: A GPU-based fiber tracking framework using geometry shaders. Proc. of SPIE Medical Imaging, Orlando, 72611J–72611J10, 2009.
Kwatra A, Prasanna V, Singh M: Accelerating DTI tractography using FPGAs. Proc. 20th International Parallel and Distributed Processing Symposium IPDPS, 1–8, 2006.
Owens JD, Luebke D, Govindaraju N, Harris M, Krüger J, Lefohn AE, Purcell TJ: A Survey of General-Purpose Computation on Graphics Hardware. Eurographics 2005, State of the Art Reports, 21–51, 2005.
PC Perspective. NVIDIA Tesla High Performance Computing—GPUs Take a New Life. Available at http://www.pcper.com/article.php?aid=424. Accessed 18 March 2009.
Buck I: GPU computing with NVIDIA CUDA. ACM SIGGRAPH 2007 courses.
NVIDIA. NVIDIA website. Available at http://www.nvidia.com/. Accessed 14 November 2008.
Mark WR, Glanville RS, Akeley K, Kilgard MJ: Cg: a system for programming graphics hardware in a C-like language. Proceedings of the ACM SIGGRAPH conference, San Diego, 896–907, 2003.
Bammer R, Auer M: Correction of eddy-current induced image warping in diffusion-weighted single-shot EPI using constrained non-rigid mutual information image registration. Proc. 9th ISMRM, Glasgow, 2001.
Skare S, Anderson JLR: Simultaneous correction of eddy currents and motion in DTI using the residual error of the diffusion tensor: comparisons with mutual information. Proc. 10th ISMRM, Hawaii, 2002.
Newegg. Available at http://www.newegg.com/. Accessed 18 March 2008.
NVIDIA. NVIDIA GeForce family. Available at http://www.nvidia.com/object/geforce_family.html. Accessed November 14, 2008.
Acknowledgments
The authors would like to thank Dr. Antonio Carlos dos Santos, from the Faculty of Medicine at Ribeirão Preto, for his help evaluating the fiber tracking tool.
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Mittmann, A., Nobrega, T.H.C., Comunello, E. et al. Performing Real-Time Interactive Fiber Tracking. J Digit Imaging 24, 339–351 (2011). https://doi.org/10.1007/s10278-009-9266-9
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DOI: https://doi.org/10.1007/s10278-009-9266-9