Multi-resolution inversion algorithm for the attenuated radon transform

Handle URI:
http://hdl.handle.net/10754/598900
Title:
Multi-resolution inversion algorithm for the attenuated radon transform
Authors:
Barbano, Paolo Emilio; Fokas, Athanasios S.
Abstract:
We 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.
Citation:
Barbano 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.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
2011 IEEE International Workshop on Machine Learning for Signal Processing
Issue Date:
Sep-2011
DOI:
10.1109/mlsp.2011.6064632
Type:
Conference Paper
Sponsors:
This work was partially funded by KAUST and EPSRC. PEB was also sponsored by the Chinese Academy of Sciences.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorBarbano, Paolo Emilioen
dc.contributor.authorFokas, Athanasios S.en
dc.date.accessioned2016-02-25T13:43:21Zen
dc.date.available2016-02-25T13:43:21Zen
dc.date.issued2011-09en
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.en
dc.identifier.doi10.1109/mlsp.2011.6064632en
dc.identifier.urihttp://hdl.handle.net/10754/598900en
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.en
dc.description.sponsorshipThis work was partially funded by KAUST and EPSRC. PEB was also sponsored by the Chinese Academy of Sciences.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectImage reconstructionen
dc.subjectMultiresolution Analysisen
dc.subjectNon-linear processingen
dc.subjectRadon transformen
dc.titleMulti-resolution inversion algorithm for the attenuated radon transformen
dc.typeConference Paperen
dc.identifier.journal2011 IEEE International Workshop on Machine Learning for Signal Processingen
dc.contributor.institutionUniversity of Cambridge, Cambridge, United Kingdomen
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