Fiber tracking using recursive stack data structure

Abstract

In diffusion tensor magnetic resonance imaging (DT-MRI), each voxel is assigned a tensor that describes local water diffusion. In this study, the eigenvectors of the diffusion tensor are analyzed based on stack linked list application. The aim of the study is to develop a reliable and rapid tractography algorithm. The analyzed image sample consists of 60 diffusion weighted human brain images and a null image namely the T2 image creating a set of intensity images of size 256×256×60×30. The eigenvectors of D is calculated in every pixel, apparent diffusion coefficient ADC is represented with respect to D. The idea of the proposed method is to accomplish the fiber pathway by starting from a single, selected node taking every node in other words all the information of the eigenvector of the whole brain into account. Via the proposed study, an elimination method for the main drawback in DTI literature namely the uncertainty regions are aimed.