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Information-theoretic analysis of brain white matter fiber orientation distribution functions. 2007

Ming-Chang Chiang, and Andrea D Klunder, and Katie McMahon, and Greig I de Zubicaray, and Margaret J Wright, and Arthur W Toga, and Paul M Thompson
Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA.

We propose a new information-theoretic metric, the symmetric Kullback-Leibler divergence (sKL-divergence), to measure the difference between two water diffusivity profiles in high angular resolution diffusion imaging (HARDI). Water diffusivity profiles are modeled as probability density functions on the unit sphere, and the sKL-divergence is computed from a spherical harmonic series, which greatly reduces computational complexity. Adjustment of the orientation of diffusivity functions is essential when the image is being warped, so we propose a fast algorithm to determine the principal direction of diffusivity functions using principal component analysis (PCA). We compare sKL-divergence with other inner-product based cost functions using synthetic samples and real HARDI data, and show that the sKL-divergence is highly sensitive in detecting small differences between two diffusivity profiles and therefore shows promise for applications in the nonlinear registration and multisubject statistical analysis of HARDI data.

UI MeSH Term Description Entries
D007089 Image Enhancement Improvement of the quality of a picture by various techniques, including computer processing, digital filtering, echocardiographic techniques, light and ultrastructural MICROSCOPY, fluorescence spectrometry and microscopy, scintigraphy, and in vitro image processing at the molecular level. Image Quality Enhancement,Enhancement, Image,Enhancement, Image Quality,Enhancements, Image,Enhancements, Image Quality,Image Enhancements,Image Quality Enhancements,Quality Enhancement, Image,Quality Enhancements, Image
D007090 Image Interpretation, Computer-Assisted Methods developed to aid in the interpretation of ultrasound, radiographic images, etc., for diagnosis of disease. Image Interpretation, Computer Assisted,Computer-Assisted Image Interpretation,Computer-Assisted Image Interpretations,Image Interpretations, Computer-Assisted,Interpretation, Computer-Assisted Image,Interpretations, Computer-Assisted Image
D007257 Information Theory An interdisciplinary study dealing with the transmission of messages or signals, or the communication of information. Information theory does not directly deal with meaning or content, but with physical representations that have meaning or content. It overlaps considerably with communication theory and CYBERNETICS. Information Theories,Theories, Information,Theory, Information
D008959 Models, Neurological Theoretical representations that simulate the behavior or activity of the neurological system, processes or phenomena; includes the use of mathematical equations, computers, and other electronic equipment. Neurologic Models,Model, Neurological,Neurologic Model,Neurological Model,Neurological Models,Model, Neurologic,Models, Neurologic
D009413 Nerve Fibers, Myelinated A class of nerve fibers as defined by their structure, specifically the nerve sheath arrangement. The AXONS of the myelinated nerve fibers are completely encased in a MYELIN SHEATH. They are fibers of relatively large and varied diameters. Their NEURAL CONDUCTION rates are faster than those of the unmyelinated nerve fibers (NERVE FIBERS, UNMYELINATED). Myelinated nerve fibers are present in somatic and autonomic nerves. A Fibers,B Fibers,Fiber, Myelinated Nerve,Fibers, Myelinated Nerve,Myelinated Nerve Fiber,Myelinated Nerve Fibers,Nerve Fiber, Myelinated
D010363 Pattern Recognition, Automated In INFORMATION RETRIEVAL, machine-sensing or identification of visible patterns (shapes, forms, and configurations). (Harrod's Librarians' Glossary, 7th ed) Automated Pattern Recognition,Pattern Recognition System,Pattern Recognition Systems
D001921 Brain The part of CENTRAL NERVOUS SYSTEM that is contained within the skull (CRANIUM). Arising from the NEURAL TUBE, the embryonic brain is comprised of three major parts including PROSENCEPHALON (the forebrain); MESENCEPHALON (the midbrain); and RHOMBENCEPHALON (the hindbrain). The developed brain consists of CEREBRUM; CEREBELLUM; and other structures in the BRAIN STEM. Encephalon
D003198 Computer Simulation Computer-based representation of physical systems and phenomena such as chemical processes. Computational Modeling,Computational Modelling,Computer Models,In silico Modeling,In silico Models,In silico Simulation,Models, Computer,Computerized Models,Computer Model,Computer Simulations,Computerized Model,In silico Model,Model, Computer,Model, Computerized,Model, In silico,Modeling, Computational,Modeling, In silico,Modelling, Computational,Simulation, Computer,Simulation, In silico,Simulations, Computer
D000465 Algorithms A procedure consisting of a sequence of algebraic formulas and/or logical steps to calculate or determine a given task. Algorithm
D001185 Artificial Intelligence Theory and development of COMPUTER SYSTEMS which perform tasks that normally require human intelligence. Such tasks may include speech recognition, LEARNING; VISUAL PERCEPTION; MATHEMATICAL COMPUTING; reasoning, PROBLEM SOLVING, DECISION-MAKING, and translation of language. AI (Artificial Intelligence),Computer Reasoning,Computer Vision Systems,Knowledge Acquisition (Computer),Knowledge Representation (Computer),Machine Intelligence,Computational Intelligence,Acquisition, Knowledge (Computer),Computer Vision System,Intelligence, Artificial,Intelligence, Computational,Intelligence, Machine,Knowledge Representations (Computer),Reasoning, Computer,Representation, Knowledge (Computer),System, Computer Vision,Systems, Computer Vision,Vision System, Computer,Vision Systems, Computer

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