Particle filters, a quasi-monte-carlo-solution for segmentation of coronaries

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

Volumn 3749 LNCS, Issue , 2005, Pages 246-253

  Florin, Charles ^a   Paragios, Nikos ^b   Williams, Jim ^a  

^a SIEMENS CORPORATE RESEARCH   (United States)

^b UNIVERSITÉ PARIS EST   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BIOFILTERS; IMAGE SEGMENTATION; MATHEMATICAL MODELS; MEDICAL IMAGING; MONTE CARLO METHODS;

CORONARIES; CORONARY ARTERIES; PARTICLE FILTERS;

BLOOD VESSELS;

ALGORITHM; ANGIOCARDIOGRAPHY; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BIOLOGICAL MODEL; COMPARATIVE STUDY; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; CORONARY ARTERY ATHEROSCLEROSIS; CORONARY BLOOD VESSEL; EVALUATION; HUMAN; IMAGE QUALITY; MAGNETIC RESONANCE ANGIOGRAPHY; METHODOLOGY; MONTE CARLO METHOD; PARTICLE SIZE; PATHOLOGY; RADIOGRAPHY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTER SIMULATION; CORONARY ANGIOGRAPHY; CORONARY ARTERIOSCLEROSIS; CORONARY VESSELS; HUMANS; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE ANGIOGRAPHY; MODELS, BIOLOGICAL; MODELS, STATISTICAL; MONTE CARLO METHOD; PARTICLE SIZE; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 33744814384     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11566465_31     Document Type: Conference Paper

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