Integration of sparse multi-modality representation and geometrical constraint for isointense infant brain segmentation

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

Volumn 8149 LNCS, Issue PART 1, 2013, Pages 703-710

  Wang, Li ^a   Shi, Feng ^a   Li, Gang ^a   Lin, Weili ^a   Gilmore, John H ^a   Shen, Dinggang ^a  

^a UNIVERSITY OF NORTH CAROLINA SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATED SEGMENTATION; DIFFUSION WEIGHTED IMAGES; GEOMETRICAL CONSTRAINTS; LEAVE-ONE-OUT CROSS VALIDATIONS; MULTI-MODALITY IMAGES; PARTIAL VOLUME EFFECT; SPARSE REPRESENTATION; STATE-OF-THE-ART METHODS;

MAGNETIC RESONANCE IMAGING; STATISTICAL METHODS;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; AUTOMATED PATTERN RECOGNITION; BRAIN; COMPUTER ASSISTED DIAGNOSIS; FEMALE; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; INFANT; MALE; METHODOLOGY; MULTIMODAL IMAGING; NEWBORN; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SYSTEM ANALYSIS;

ALGORITHMS; BRAIN; FEMALE; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; INFANT; INFANT, NEWBORN; MAGNETIC RESONANCE IMAGING; MALE; MULTIMODAL IMAGING; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SYSTEMS INTEGRATION;

EID: 84892872033     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-40811-3_88     Document Type: Conference Paper

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