Effective statistical edge integration using a flux maximizing scheme for volumetric vascular segmentation in MRA

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

Volumn 4584 LNCS, Issue , 2007, Pages 86-97

  Gooya, Ali ^a   Liao, Hongen ^a   Matsumiya, Kiyoshi ^a   Masamune, Ken ^a   Dohi, Takeyoshi ^a  

^a UNIVERSITY OF TOKYO   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ANGIOGRAPHY; BLOOD VESSELS; EVOLUTIONARY ALGORITHMS; MEDICAL IMAGING; STATISTICAL METHODS; VARIATIONAL TECHNIQUES;

EDGE STRENGTH EFFECT; ENERGY MINIMIZATION; LEVEL SET THEORY; MAGNETIC RESONANCE ANGIOGRAPHY; STATISTICAL EDGE INTEGRATION;

IMAGE SEGMENTATION;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; EVALUATION; HUMAN; IMAGE ENHANCEMENT; MAGNETIC RESONANCE ANGIOGRAPHY; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL ANALYSIS; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE ANGIOGRAPHY; MODELS, CARDIOVASCULAR; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 34548389341     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73273-0_8     Document Type: Conference Paper

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