Analytical reconstructions for PET and spect employing L$^{1}$-denoising

PE. Barbano; A.S. Fokas; G.A. Kastis

doi:10.1109/icdsp.2009.5201187

Analytical reconstructions for PET and spect employing L$^{1}$-denoising

PE. Barbano, A.S. Fokas, G.A. Kastis

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

We propose an efficient, deterministic algorithm designed to reconstruct images from real Radon-Transform and Attenuated Radon-Transform data. Its input consists in a small family of recorded signals, each sampling the same composite photon or positron emission scene over a non-Gaussian, noisy channel. The reconstruction is performed by combining a novel numerical implementation of an analytical inversion formula [1] and a novel signal processing technique, inspired by the work of Tao and Candes [2] on code reconstruction. Our approach is proven to be optimal under a variety of realistic assumptions. We also indicate several medical imaging applications for which the new technology achieves high fidelity, even when dealing with real data subject to substantial non-Gaussian distortions. © 2009 IEEE.

Original language	English (US)
Title of host publication	2009 16th International Conference on Digital Signal Processing
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
ISBN (Print)	9781424432974
DOIs	https://doi.org/10.1109/icdsp.2009.5201187
State	Published - Jul 2009
Externally published	Yes

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was partially funded by KAUST. We are also grateful to Captain V. Constantakopoulos for his generous support.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.

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10.1109/icdsp.2009.5201187

Cite this

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title = "Analytical reconstructions for PET and spect employing L$^{1}$-denoising",

abstract = "We propose an efficient, deterministic algorithm designed to reconstruct images from real Radon-Transform and Attenuated Radon-Transform data. Its input consists in a small family of recorded signals, each sampling the same composite photon or positron emission scene over a non-Gaussian, noisy channel. The reconstruction is performed by combining a novel numerical implementation of an analytical inversion formula [1] and a novel signal processing technique, inspired by the work of Tao and Candes [2] on code reconstruction. Our approach is proven to be optimal under a variety of realistic assumptions. We also indicate several medical imaging applications for which the new technology achieves high fidelity, even when dealing with real data subject to substantial non-Gaussian distortions. {\textcopyright} 2009 IEEE.",

author = "PE. Barbano and A.S. Fokas and G.A. Kastis",

note = "KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This work was partially funded by KAUST. We are also grateful to Captain V. Constantakopoulos for his generous support. This publication acknowledges KAUST support, but has no KAUST affiliated authors.",

year = "2009",

month = jul,

doi = "10.1109/icdsp.2009.5201187",

language = "English (US)",

isbn = "9781424432974",

booktitle = "2009 16th International Conference on Digital Signal Processing",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

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T1 - Analytical reconstructions for PET and spect employing L$^{1}$-denoising

AU - Barbano, PE.

AU - Fokas, A.S.

AU - Kastis, G.A.

N1 - KAUST Repository Item: Exported on 2020-10-01 Acknowledgements: This work was partially funded by KAUST. We are also grateful to Captain V. Constantakopoulos for his generous support. This publication acknowledges KAUST support, but has no KAUST affiliated authors.

PY - 2009/7

Y1 - 2009/7

N2 - We propose an efficient, deterministic algorithm designed to reconstruct images from real Radon-Transform and Attenuated Radon-Transform data. Its input consists in a small family of recorded signals, each sampling the same composite photon or positron emission scene over a non-Gaussian, noisy channel. The reconstruction is performed by combining a novel numerical implementation of an analytical inversion formula [1] and a novel signal processing technique, inspired by the work of Tao and Candes [2] on code reconstruction. Our approach is proven to be optimal under a variety of realistic assumptions. We also indicate several medical imaging applications for which the new technology achieves high fidelity, even when dealing with real data subject to substantial non-Gaussian distortions. © 2009 IEEE.

AB - We propose an efficient, deterministic algorithm designed to reconstruct images from real Radon-Transform and Attenuated Radon-Transform data. Its input consists in a small family of recorded signals, each sampling the same composite photon or positron emission scene over a non-Gaussian, noisy channel. The reconstruction is performed by combining a novel numerical implementation of an analytical inversion formula [1] and a novel signal processing technique, inspired by the work of Tao and Candes [2] on code reconstruction. Our approach is proven to be optimal under a variety of realistic assumptions. We also indicate several medical imaging applications for which the new technology achieves high fidelity, even when dealing with real data subject to substantial non-Gaussian distortions. © 2009 IEEE.

UR - http://hdl.handle.net/10754/597569

UR - http://ieeexplore.ieee.org/document/5201187/

UR - http://www.scopus.com/inward/record.url?scp=70449597609&partnerID=8YFLogxK

U2 - 10.1109/icdsp.2009.5201187

DO - 10.1109/icdsp.2009.5201187

M3 - Conference contribution

SN - 9781424432974

BT - 2009 16th International Conference on Digital Signal Processing

PB - Institute of Electrical and Electronics Engineers (IEEE)

ER -

Analytical reconstructions for PET and spect employing L$^{1}$-denoising

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Bibliographical note

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