Measures for pathway analysis in brain white matter using diffusion tensor images

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4584 LNCS, Issue , 2007, Pages 642-649

  Astola, Laura ^a   Florack, Luc ^a   Haar Romeny, Bart Ter ^a  

^a EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Brain white matter connectivity; DTI; Geodesic deviation; Geodesies; Ricci tensor; Riemann tensor

Indexed keywords

BRAIN; GEODESY; MAGNETIC RESONANCE IMAGING;

BRAIN WHITE MATTER; CONNECTIVITY ANALYSIS; GEODESIC DEVIATION; RICCI TENSOR; RIEMANN TENSOR; RIEMANNIAN GEOMETRY;

MEDICAL IMAGING;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; CYTOLOGY; DIFFUSION WEIGHTED IMAGING; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; MYELINATED NERVE; NERVE TRACT; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING; ULTRASTRUCTURE;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; NERVE FIBERS, MYELINATED; NEURAL PATHWAYS; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 38149127163     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73273-0_53     Document Type: Conference Paper

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