Title :
Fiber Tracking: A Recursive Stack Algorithmic Approach
Author :
Duru, Dilek Goksel ; Ozkan, M.
Author_Institution :
Bogazici Univ., Istanbul
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 and eigenvalues of the diffusion tensor D are analyzed based on stack linked list algorithm. The aim of the study is to develop a reliable and rapid tractography algorithm. In our sample, 60 diffusion weighted human brain images and a null image namely the T2 image creating a set of intensity images of size 256 times 256 times 60 times 30 have been examined. The eigensystem 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 eigensystem of the whole brain into account. Developing a reliable and rapid fiber tracking algorithm for the clinical use regarding to the verified results is the future study of the work in progress.
Keywords :
biomedical MRI; brain; eigenvalues and eigenfunctions; medical image processing; DT-MRI; brain images; diffusion tensor magnetic resonance imaging; eigenvalues; eigenvectors; fiber tracking; local water diffusion; recursive stack algorithm; stack linked list algorithm; tractography algorithm; Anisotropic magnetoresistance; Diffusion tensor imaging; Eigenvalues and eigenfunctions; Ellipsoids; Equations; Principal component analysis; Symmetric matrices; Tensile stress; Transmission line matrix methods; Weight measurement; Algorithms; Brain; Diffusion Magnetic Resonance Imaging; Humans; Nerve Fibers; Principal Component Analysis;
Conference_Titel :
Engineering in Medicine and Biology Society, 2007. EMBS 2007. 29th Annual International Conference of the IEEE
Conference_Location :
Lyon
Print_ISBN :
978-1-4244-0787-3
DOI :
10.1109/IEMBS.2007.4352287