A Proposed algorithm for diffusion magnetic resonance imaging brain tractography

Abstract

Most of previously published diffusion magnetic resonance imaging reconstruction methods are linked to their own track integration method, some of them use Euler integration others try to improve the integration using the second order and the fourth-order Rang Kutta algorithms. In this work, we have formulated a general, deterministic tractography algorithm (CIERTE), which is a combination of Improved Euler and Range-Kutta fourth-order algorithm, which combine the speed and accuracy at the same time. We have used also trilinear interpolation, which works with voxel level information about fiber orientations including multiple crossings, and employs a range of stopping criteria as those described in EuDX [1] algorithm and FACT [2]. The purpose of this algorithm is to make tracking accurate and fast at the same time and make it general for all deterministic tracking methods.