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dc.contributor.authorBarbano, Paolo Emilio
dc.contributor.authorFokas, Athanasios S.
dc.date.accessioned2016-02-25T13:43:21Z
dc.date.available2016-02-25T13:43:21Z
dc.date.issued2011-09
dc.identifier.citationBarbano PE, Fokas AS (2011) Multi-resolution inversion algorithm for the attenuated radon transform. 2011 IEEE International Workshop on Machine Learning for Signal Processing. Available: http://dx.doi.org/10.1109/mlsp.2011.6064632.
dc.identifier.doi10.1109/mlsp.2011.6064632
dc.identifier.urihttp://hdl.handle.net/10754/598900
dc.description.abstractWe present a FAST implementation of the Inverse Attenuated Radon Transform which incorporates accurate collimator response, as well as artifact rejection due to statistical noise and data corruption. This new reconstruction procedure is performed by combining a memory-efficient implementation of the analytical inversion formula (AIF [1], [2]) with a wavelet-based version of a recently discovered regularization technique [3]. The paper introduces all the main aspects of the new AIF, as well numerical experiments on real and simulated data. Those display a substantial improvement in reconstruction quality when compared to linear or iterative algorithms. © 2011 IEEE.
dc.description.sponsorshipThis work was partially funded by KAUST and EPSRC. PEB was also sponsored by the Chinese Academy of Sciences.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectImage reconstruction
dc.subjectMultiresolution Analysis
dc.subjectNon-linear processing
dc.subjectRadon transform
dc.titleMulti-resolution inversion algorithm for the attenuated radon transform
dc.typeConference Paper
dc.identifier.journal2011 IEEE International Workshop on Machine Learning for Signal Processing
dc.contributor.institutionUniversity of Cambridge, Cambridge, United Kingdom


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