Diffusion-based population statistics using tract probability maps

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

Volumn 6361 LNCS, Issue PART 1, 2010, Pages 631-639

  Wassermann, Demian ^a   Kanterakis, Efstathios ^b   Gur, Ruben C ^c   Deriche, Rachid ^a   Verma, Ragini ^b  

^a INRIA   (France)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c HOSPITAL OF THE UNIVERSITY OF PENNSYLVANIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED ANALYSIS; DIFFUSION IMAGING; FUNCTION MAPPING; GAUSSIAN PROCESSES; HEALTHY CONTROLS; MEDIAL REPRESENTATION; NOVEL TECHNIQUES; PROBABILITY MAPS; SCHIZOPHRENIA PATIENTS; SENSITIVITY AND SPECIFICITY; SHEET-LIKE; STATISTICAL ANALYSIS; STATISTICAL DIFFERENCES; TRACTOGRAPHY; WHITE MATTER;

DIFFUSION; MEDICAL COMPUTING; MEDICAL IMAGING; PROBABILITY; PROBABILITY DENSITY FUNCTION; STATISTICAL METHODS; THERMOELECTRIC POWER; VISUALIZATION;

POPULATION STATISTICS;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; DIFFUSION TENSOR IMAGING; HISTOLOGY; IMAGE ENHANCEMENT; METHODOLOGY; MYELINATED NERVE; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; ULTRASTRUCTURE;

ALGORITHMS; BRAIN; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; DIFFUSION TENSOR IMAGING; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MODELS, NEUROLOGICAL; MODELS, STATISTICAL; NERVE FIBERS, MYELINATED; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 78349280322     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15705-9_77     Document Type: Conference Paper

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