Towards whole brain segmentation by a hybrid model

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

Volumn 4792 LNCS, Issue PART 2, 2007, Pages 169-177

  Tu, Zhuowen ^a   Toga, Arthur W ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; BRAIN; MAGNETIC RESONANCE IMAGING; PATTERN RECOGNITION;

BRAIN SEGMENTATION ALGORITHMS; EDGE FIELD; PROBABILISTIC BOOSTING TREE (PBT);

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; BRAIN; CLUSTER ANALYSIS; COMPUTER ASSISTED DIAGNOSIS; DIFFUSION WEIGHTED IMAGING; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BRAIN; CLUSTER ANALYSIS; DIFFUSION MAGNETIC RESONANCE IMAGING; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 84857164420     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75759-7_21     Document Type: Conference Paper

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