4-D generative model for PET/MRI reconstruction

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

Volumn 6891 LNCS, Issue PART 1, 2011, Pages 581-588

  Pedemonte, Stefano ^a   Bousse, Alexandre ^b   Hutton, Brian F ^b   Arridge, Simon ^a   Ourselin, Sebastien ^a  

^a UNIVERSITY COLLEGE LONDON   (United Kingdom)

^b UNIVERSITY COLLEGE LONDON HOSPITALS   (United Kingdom)

Author keywords

Bayesian Networks; Emission Tomography; Molecular Imaging; Motion correction; Multi modality

Indexed keywords

BRAIN PHANTOMS; EMISSION TOMOGRAPHY; GENERATIVE MODEL; HEAD MOVEMENTS; ITERATIVE ALGORITHM; JOINT ESTIMATION; MIXTURE OF GAUSSIANS; MOLECULAR IMAGING; MOTION CORRECTION; MOTION PARAMETERS; MRI IMAGE; MULTI-MODALITY; OPTIMISATIONS; PROBABILISTIC MODELS; SIMULATION DATA; TIME-DEPENDENT ACTIVITY;

ALGORITHMS; BAYESIAN NETWORKS; ESTIMATION; MAGNETIC RESONANCE IMAGING; MEDICAL COMPUTING; MEDICAL IMAGING;

THREE DIMENSIONAL;

ALGORITHM; ARTICLE; BAYES THEOREM; BRAIN; BRAIN MAPPING; COMPUTER PROGRAM; COMPUTER SIMULATION; FACTUAL DATABASE; HUMAN; IMAGE PROCESSING; IMAGE QUALITY; METHODOLOGY; MOTION; NORMAL DISTRIBUTION; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; POSITRON EMISSION TOMOGRAPHY; PROBABILITY; STATISTICAL MODEL; THREE DIMENSIONAL IMAGING;

ALGORITHMS; BAYES THEOREM; BRAIN; BRAIN MAPPING; COMPUTER SIMULATION; DATABASES, FACTUAL; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; IMAGING, THREE-DIMENSIONAL; MAGNETIC RESONANCE IMAGING; MARKOV CHAINS; MODELS, STATISTICAL; MOTION; NORMAL DISTRIBUTION; PHANTOMS, IMAGING; POSITRON-EMISSION TOMOGRAPHY; SOFTWARE;

EID: 82255183364     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-23623-5_73     Document Type: Conference Paper

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