%0 Journal Article
%T Determination of Neural Fiber Connections Based on Data Structure Algorithm
%A Dilek G£¿ksel Duru
%A Mehmed £¿zkan
%J Computational Intelligence and Neuroscience
%D 2010
%I Hindawi Publishing Corporation
%R 10.1155/2010/251928
%X The brain activity during perception or cognition is mostly examined by functional magnetic resonance imaging (fMRI). However, the cause of the detected activity relies on the anatomy. Diffusion tensor magnetic resonance imaging (DTMRI) as a noninvasive modality providing in vivo anatomical information allows determining neural fiber connections which leads to brain mapping. Still a complete map of fiber paths representing the human brain is missing in literature. One of the main drawbacks of reliable fiber mapping is the correct detection of the orientation of multiple fibers within a single imaging voxel. In this study a method based on linear data structures is proposed to define the fiber paths regarding their diffusivity. Another advantage of the proposed method is that the analysis is applied on entire brain diffusion tensor data. The implementation results are promising, so that the method will be developed as a rapid fiber tractography algorithm for the clinical use as future study. 1. Introduction Functional magnetic resonance imaging (fMRI) serves to determine the brain activity during perception or cognition. BOLD contrast for fMRI is remarkable in cognitive neuroscience, surgical treatment planning, and preclinical studies in examining the main parameters such as the blood flow, blood volume, resting state connectivity, and anatomical connectivity within the brain [1]. To define the cause of the detected activity, the anatomy of the underlying tissue must be analyzed. The functional properties of the region of interests (ROIs) in the brain can be investigated by combination of different modalities such as diffusion tensor magnetic resonance imaging (DTMRI or DTI), ADC fMRI, and BOLD fMRI [2]. As a noninvasive imaging modality DTMRI helps identification and visualization of the fiber connections in the anatomy [3¨C5]. DTMRI is unique in its ability providing in-vivo anatomical information noninvasively. The potential of DTI is to make the determination of anatomical connectivity in the investigated brain regions by mapping the axonal pathways in white matter noninvasively [6]. The lack of a complete neural fiber map in literature makes the postprocessing of the data very important. Methods and updates are to be researched to define the fiber trajectories in the uncertainty regions where multiple fiber orientations cross within a single imaging voxel [7, 8]. Our proposed technique aims to track the white matter fibers according to data structure algorithm noniteratively and depending on the structural information of the underlying tissue. The
%U http://www.hindawi.com/journals/cin/2010/251928/