Attenuation resilient AIF estimation based on hierarchical bayesian modelling for first pass myocardial perfusion MRI

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

Volumn 4791 LNCS, Issue PART 1, 2007, Pages 393-400

  Schmid, Volker J ^a   Gatehouse, Peter D ^b   Yang, Guang Zhong ^a  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b ROYAL BROMPTON HOSPITAL   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

BAYESIAN NETWORKS; BLOOD; COMPUTER SIMULATION; DECONVOLUTION; IMAGE RECONSTRUCTION; MAGNETIC RESONANCE IMAGING;

ARTERIAL INPUT FUNCTION (AIF); CLINICAL IMPACT; CONTRAST AGENT; HIERARCHICAL BAYESIAN MODEL (HBM);

BLOOD VESSELS;

ALGORITHM; ARTICLE; ARTIFACT; ARTIFICIAL INTELLIGENCE; AUTOMATED PATTERN RECOGNITION; BAYES THEOREM; BIOLOGICAL MODEL; COMPUTER ASSISTED DIAGNOSIS; COMPUTER SIMULATION; HEART LEFT VENTRICLE FUNCTION; HUMAN; IMAGE ENHANCEMENT; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; ARTIFACTS; ARTIFICIAL INTELLIGENCE; BAYES THEOREM; COMPUTER SIMULATION; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MODELS, CARDIOVASCULAR; MODELS, STATISTICAL; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; VENTRICULAR DYSFUNCTION, LEFT;

EID: 38149139411     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-75757-3_48     Document Type: Conference Paper

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