Measuring brain variability via sulcal lines registration: A diffeomorphic approach

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

Volumn 4791 LNCS, Issue PART 1, 2007, Pages 675-682

  Durrleman, Stanley ^a,b   Pennec, Xavier ^a   Trouvé, Alain ^b   Ayache, Nicholas ^a  

^a INRIA   (France)

^b UNIVERSITÉ PARIS SACLAY   (France)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; DATABASE SYSTEMS; IMAGE REGISTRATION; MATHEMATICAL MODELS; MEDICAL IMAGING; PRINCIPAL COMPONENT ANALYSIS;

TANGENT PCA ANALYSIS; TENSORS EXTRAPOLATION;

BRAIN;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN CORTEX; COMPUTER ASSISTED DIAGNOSIS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CEREBRAL CORTEX; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SUBTRACTION TECHNIQUE;

EID: 38149068973     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75757-3_82     Document Type: Conference Paper

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