Towards accurate, automatic segmentation of the hippocampus and amygdala from MRI

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

Volumn 5762 LNCS, Issue PART 2, 2009, Pages 592-600

  Collins, D Louis ^a,b   Pruessner, Jens C ^a,c  

^a MCGILL UNIVERSITY   (Canada)

^b MCGILL UNIVERSITY   (Canada)

^c MCGILL UNIVERSITY   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

ATLAS-BASED METHODS; AUTOMATIC SEGMENTATIONS; DATA SETS; FUSION METHODS; FUSION TECHNIQUES; GOLD STANDARDS; HUMAN SUBJECTS; INVERSE TRANSFORMATIONS; NON-LINEAR; NORMAL CONTROLS; SEGMENTATION SCHEME; TEMPLATE-BASED;

ANIMALS; LABELS;

MEDICAL COMPUTING;

ALGORITHM; AMYGDALOID NUCLEUS; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; COMPUTER ASSISTED DIAGNOSIS; HIPPOCAMPUS; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; AMYGDALA; ARTIFICIAL INTELLIGENCE; HIPPOCAMPUS; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84883839307     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-04271-3_72     Document Type: Conference Paper

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