Reversible jump Markov chain Monte Carlo for Bayesian deconvolution of point sources

Proceedings of SPIE - The International Society for Optical Engineering

Volumn 3459, Issue , 1998, Pages 179-190

  Stawinski, Guillaume ^a   Doucet, Arnaud ^b   Duvaut, Patrick ^c  

^a CEA SACLAY   (France)

^b UNIVERSITY OF CAMBRIDGE   (United Kingdom)

^c ENSEA   (France)

Author keywords

Bayesian deconvolution; Bayesian inference; Nuclear imaging; Reversible jump Markov chain Monte Carlo methods

Indexed keywords

CONVOLUTION; DIFFERENTIAL EQUATIONS; FUNCTIONS; HIDDEN MARKOV MODELS; IMAGE SEGMENTATION; INFERENCE ENGINES; INTELLIGENT ROBOTS; INVERSE PROBLEMS; MARKOV PROCESSES; MATHEMATICAL MODELS; MEDICAL IMAGING; MONTE CARLO METHODS; NEMATIC LIQUID CRYSTALS; OPTICAL TRANSFER FUNCTION; SYSTEMS ANALYSIS; TRELLIS CODES; UNCERTAIN SYSTEMS;

ANALYTICAL EXPRESSIONS; BAYESIAN APPROACHES; BAYESIAN DECONVOLUTION; BAYESIAN INFERENCE; BAYESIAN MODELS; CLOSED FORMS; GAUSSIAN SHAPES; LEVEL MODELS; MARKOV CHAINS; MARKOV RANDOM FIELD MODELS; MARKOV RANDOM FIELDS; MCMC ALGORITHMS; MONTE CARLO; NUCLEAR IMAGING; POINT SOURCES; POINT SPREAD FUNCTIONS; POISSONIAN STATISTICS; POSTERIOR DISTRIBUTIONS; PRIOR DISTRIBUTIONS; PRIOR MODELS; REVERSIBLE JUMP MARKOV CHAIN MONTE CARLO METHODS; SYNTHETIC AND REAL DATUMS; UNKNOWN PARAMETERS;

BAYESIAN NETWORKS;

EID: 0001726283     PISSN: 0277786X     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1117/12.323798     Document Type: Conference Paper

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