Bayesian tracking of elongated structures in 3D images

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

Volumn 4584 LNCS, Issue , 2007, Pages 74-85

  Schaap, Michiel ^a   Smal, Ihor ^a   Metz, Coert ^a   Van Walsum, Theo ^a   Niessen, Wiro ^a  

^a ERASMUS MEDICAL CENTER   (Netherlands)

Author keywords

Bayesian tracking; CTA; Efficient; High noise

Indexed keywords

ALGORITHMS; BAYESIAN NETWORKS; COMPUTATIONAL EFFICIENCY; GAUSSIAN NOISE (ELECTRONIC); MEDICAL IMAGING;

A PRIORI KNOWLEDGE; BAYESIAN TRACKING; PROBABILISTIC TUBE TRACKING; SYNTHETIC DATA;

IMAGE ANALYSIS;

ALGORITHM; ANGIOGRAPHY; ARTICLE; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER ASSISTED TOMOGRAPHY; COMPUTER SIMULATION; EVALUATION; HUMAN; IMAGE QUALITY; METHODOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ANGIOGRAPHY; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; HUMANS; IMAGING, THREE-DIMENSIONAL; MODELS, CARDIOVASCULAR; PATTERN RECOGNITION, AUTOMATED; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TOMOGRAPHY, X-RAY COMPUTED;

EID: 38149088193     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-73273-0_7     Document Type: Conference Paper

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