A General Local Reconstruction Approach Based on a Truncated Hilbert Transform

Exact image reconstruction from limited projection data has been a central topic in the computed tomography (CT) field. In this paper, we present a general region-of-interest/volume-of-interest (ROI/VOI) reconstruction approach using a truly truncated Hilbert transform on a line-segment inside a com...

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Detalles Bibliográficos
Autores principales: Ye, Yangbo, Yu, Hengyong, Wei, Yuchuan, Wang, Ge
Formato: Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2007
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1987387/
https://www.ncbi.nlm.nih.gov/pubmed/18256734
http://dx.doi.org/10.1155/2007/63634
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author Ye, Yangbo
Yu, Hengyong
Wei, Yuchuan
Wang, Ge
author_facet Ye, Yangbo
Yu, Hengyong
Wei, Yuchuan
Wang, Ge
author_sort Ye, Yangbo
collection PubMed
description Exact image reconstruction from limited projection data has been a central topic in the computed tomography (CT) field. In this paper, we present a general region-of-interest/volume-of-interest (ROI/VOI) reconstruction approach using a truly truncated Hilbert transform on a line-segment inside a compactly supported object aided by partial knowledge on one or both neighboring intervals of that segment. Our approach and associated new data sufficient condition allows the most flexible ROI/VOI image reconstruction from the minimum account of data in both the fan-beam and cone-beam geometry. We also report primary numerical simulation results to demonstrate the correctness and merits of our finding. Our work has major theoretical potentials and innovative practical applications.
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spelling pubmed-19873872008-02-06 A General Local Reconstruction Approach Based on a Truncated Hilbert Transform Ye, Yangbo Yu, Hengyong Wei, Yuchuan Wang, Ge Int J Biomed Imaging Research Article Exact image reconstruction from limited projection data has been a central topic in the computed tomography (CT) field. In this paper, we present a general region-of-interest/volume-of-interest (ROI/VOI) reconstruction approach using a truly truncated Hilbert transform on a line-segment inside a compactly supported object aided by partial knowledge on one or both neighboring intervals of that segment. Our approach and associated new data sufficient condition allows the most flexible ROI/VOI image reconstruction from the minimum account of data in both the fan-beam and cone-beam geometry. We also report primary numerical simulation results to demonstrate the correctness and merits of our finding. Our work has major theoretical potentials and innovative practical applications. Hindawi Publishing Corporation 2007 2007-06-18 /pmc/articles/PMC1987387/ /pubmed/18256734 http://dx.doi.org/10.1155/2007/63634 Text en Copyright © 2007 Yangbo Ye et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Ye, Yangbo
Yu, Hengyong
Wei, Yuchuan
Wang, Ge
A General Local Reconstruction Approach Based on a Truncated Hilbert Transform
title A General Local Reconstruction Approach Based on a Truncated Hilbert Transform
title_full A General Local Reconstruction Approach Based on a Truncated Hilbert Transform
title_fullStr A General Local Reconstruction Approach Based on a Truncated Hilbert Transform
title_full_unstemmed A General Local Reconstruction Approach Based on a Truncated Hilbert Transform
title_short A General Local Reconstruction Approach Based on a Truncated Hilbert Transform
title_sort general local reconstruction approach based on a truncated hilbert transform
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1987387/
https://www.ncbi.nlm.nih.gov/pubmed/18256734
http://dx.doi.org/10.1155/2007/63634
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