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.
Subject(s)
Brain/anatomy & histology , Computer Graphics , Diffusion Magnetic Resonance Imaging/methods , Image Processing, Computer-Assisted/methods , Nerve Fibers, Myelinated , Algorithms , Feasibility Studies , HumansABSTRACT
Diffusion tensor magnetic resonance imaging has been successfully applied to the process of fiber tracking, which determines the location of fiber bundles within the human brain. This process, however, can be quite lengthy when run on a regular workstation. We present a means of executing this process by making use of the graphics processing units of computers' video cards, which provide a low-cost parallel execution environment that algorithms like fiber tracking can benefit from. With this method we have achieved performance gains varying from 14 to 40 times on common computers. Because of accuracy issues inherent to current graphics processing units, we define a variation index in order to assess how close the results obtained with our method are to those generated by programs running on the central processing units of computers. This index shows that results produced by our method are acceptable when compared to those of traditional programs.
