Analysis of brain white matter via fiber tract modeling

• Published in: Conference proceedings (IEEE Engineering in Medicine and Biology Society. Conf.) Vol. 2; no. 5; pp. 4421 - 4424
• Main Authors: Gerig, G., Gouttard, S., Corouge, I.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 2004; Institute of Electrical and Electronics Engineers (IEEE)
• Subjects: Algorithms; Anisotropic magnetoresistance; Artificial Intelligence; Brain; Brain modeling; Clinical diagnosis; Computer architecture; Computer Science; Computer Simulation; Diffusion Magnetic Resonance Imaging; Diffusion tensor imaging; Engineering Sciences; Feasibility Studies; Humans; Image Enhancement; Image Interpretation, Computer-Assisted; Image Processing; Imaging, Three-Dimensional; Information Storage and Retrieval; Life Sciences; Medical Imaging; Models, Neurological; Models, Statistical; Neural Pathways; Neurons and Cognition; Pattern analysis; Pattern Recognition, Automated; Psychiatry; Reproducibility of Results; Sensitivity and Specificity; Signal and Image processing; Tensile stress; DTI analysis; Fiber tract modeling; Diffusion tensor interpolation; diffusion tensor statistics
• ISBN: 9780780384392; 0780384393
• ISSN: 1557-170X
• DOI: 10.1109/IEMBS.2004.1404229

White matter fiber bundles of the human brain form a spatial pattern defined by the anatomical and functional architecture. Tractography applied to the tensor field in diffusion tensor imaging (DTI) results in sets of streamlines which can be associated with major fiber tracts. Comparison of fiber tract properties across subjects needs comparison at corresponding anatomical locations. Moreover, clinical analysis studying fiber tract disruption and integrity requires analysis along tracts and within cross-sections, which is hard to accomplish by conventional region of interest and voxel-based analysis. We propose a new framework for MR DTI analysis that includes tractography, fiber clustering, alignment via local shape parametrization and diffusion analysis across and along tracts. Feasibility is shown with the uncinate fasciculus and the cortico-spinal tracts. The extended set of features including fiber tract geometry and diffusion properties might lead to an improved understanding of diffusion properties and its association to normal/abnormal brain development.