Real-Time Fine-Tuned Adjustment of Fiber Tracking Parameters

Abstract

Fiber tracking is a mature technique that aids neurosurgeons by providing the location of neuronal fibers in a patient's brain. Although the interactivity of tools have been typically limited, the exploitation of the parallel nature of fiber tracking is rapidly changing this landscape. The parallel environment offered by GPUs and modern CPUs enables fiber tracking to be executed very quickly on consumer-grade computers. The adjustment of fiber tracking parameters can currently be made on the fly, and the new results can be both computed and displayed in real-time on the screen. In order to further improve the interactivity of fiber tracking tools, this article proposes the application of histogram equalization, a traditional digital image processing procedure, to the fiber tracking parameters. The non-linear scale obtained by this process allows the user to interactively explore sensitive regions of the parameter space. Results show that this scale can be computed in real-time and that it can be cleanly integrated into fiber tracking tools.