Computer Science – Information Theory
Scientific paper
May 2001
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2001aipc..568..513e&link_type=abstract
BAYESIAN INFERENCE AND MAXIMUM ENTROPY METHODS IN SCIENCE AND ENGINEERING: 20th International Workshop. AIP Conference Proceedi
Computer Science
Information Theory
Medical Imaging Equipment, Image Processing, Information Theory And Communication Theory, Instruments For Environmental Pollution Measurements
Scientific paper
In scintigraphic imaging, among all undesirable effects, photon scattering is undoubtedly the biggest problem. This leads to an apparent spreading of the gamma-ray sources over large areas, a wrong detection of the source location and a contrast loss. These drawbacks are especially penalizing when detecting small details. We propose an image restoration method taking fully into account the scattered photons. This method is based on the multi-energy image formation model which we have previously propounded. Moreover, the restoration method is developed in the Bayesian framework with a Markovian discontinuity-preserving regularization. This enhances the detectability of small details, which is essential in medical applications. .
Eglin L.
Faye Christian
Nguyen Mai K.
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