Liver segmentation using sparse 3D prior models with optimal data support

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

Volumn 4584 LNCS, Issue , 2007, Pages 38-49

  Florin, Charles ^a   Paragios, Nikos ^b   Funka Lea, Gareth ^a   Williams, James ^c  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b Ecole Centrale de Paris   (France)

^c SIEMENS AG   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL ORGANS; DATA REDUCTION; INFORMATION USE; MATHEMATICAL MODELS; MEDICAL IMAGING; STATISTICAL METHODS;

KNOWLEDGE STATISTICS; LIVER SEGMENTATION; SPARSE INFORMATION MODEL;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; COMPUTER SIMULATION; EVALUATION; FACTUAL DATABASE; HUMAN; IMAGE QUALITY; INFORMATION RETRIEVAL; LIVER; METHODOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATABASES, FACTUAL; HUMANS; IMAGING, THREE-DIMENSIONAL; INFORMATION STORAGE AND RETRIEVAL; LIVER; MODELS, BIOLOGICAL; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 34548414140     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73273-0_4     Document Type: Conference Paper

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