3D knowledge-based segmentation using pose-invariant higher-order graphs

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

Volumn 6363 LNCS, Issue PART 3, 2010, Pages 189-196

  Wang, Chaohui ^a,b   Teboul, Olivier ^a,c   Michel, Fabrice ^a,b   Essafi, Salma ^a,b   Paragios, Nikos ^a,b  

^a Ecole Centrale de Paris   (France)

^b INRIA SACLAY   (France)

^c MICROSOFT   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ENCODING (SYMBOLS); KNOWLEDGE BASED SYSTEMS; LEARNING SYSTEMS; MARKOV PROCESSES; MEDICAL IMAGING;

DUAL DECOMPOSITION; HIGHER ORDER TERMS; INFERENCE METHODS; KNOWLEDGE BASED; MARKOV RANDOM FIELD MODELS; OPTIMAL SOLUTIONS; PRIOR KNOWLEDGE; TRAINING EXAMPLE;

IMAGE SEGMENTATION;

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

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

EID: 80055033033     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-15711-0_24     Document Type: Conference Paper

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