Spine detection and labeling using a parts-based graphical model

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

Volumn 4584 LNCS, Issue , 2007, Pages 122-133

  Schmidt, Stefan ^a,b   Kappes, Jörg ^b   Bergtholdt, Martin ^b   Pekar, Vladimir ^a   Dries, Sebastian ^a   Bystrov, Daniel ^a   Schnörr, Christoph ^b  

^a PHILIPS RESEARCH LABORATORIES   (Germany)

^b UNIVERSITY OF MANNHEIM   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

COMBINATORIAL OPTIMIZATION; COMPUTATIONAL COMPLEXITY; FEATURE EXTRACTION; MAGNETIC RESONANCE IMAGING; MATHEMATICAL MODELS; STATISTICAL METHODS;

ANATOMICAL STRUCTURES; CONTEXTUAL SHAPE KNOWLEDGE; PROBABILISTIC GRAPHICAL MODEL; SPINE DETECTION;

IMAGE ANALYSIS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER GRAPHICS; COMPUTER SIMULATION; EVALUATION; HISTOLOGY; HUMAN; IMAGE ENHANCEMENT; IMAGE SUBTRACTION; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SPINE; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER GRAPHICS; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPINE; SUBTRACTION TECHNIQUE;

EID: 34548426103     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73273-0_11     Document Type: Conference Paper

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