Fully automatic segmentation of the hippocampus and the amygdala from MRI using hybrid prior knowledge

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 875-882

  Chupin, Marie ^a,b   Hammers, Alexander ^c   Bardinet, Eric ^b   Colliot, Olivier ^b   Liu, Rebecca S N ^d   Duncan, John S ^a   Garnero, Line ^b   Lemieux, Louis ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b Centre National de la Recherche Scientifique   (France)

^c Department of Electrical and Electronic Engineering   (United Kingdom)

^d NATIONAL HOSPITAL FOR NEUROLOGY AND NEUROSURGERY   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

CONSTRAINT THEORY; ERROR ANALYSIS; IMAGE REGISTRATION; MAGNETIC RESONANCE IMAGING;

ANATOMICAL LANDMARKS; AUTOMATIC SEGMENTATION;

IMAGE SEGMENTATION;

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

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

EID: 79551686403     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75757-3_106     Document Type: Conference Paper

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