A General Local Reconstruction Approach Based on a Truncated Hilbert Transform | Zendy

Yangbo Ye | Zendy; Hengyong Yu | Zendy; Yuchuan Wei | Zendy; Ge Wang | Zendy

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A General Local Reconstruction Approach Based on a Truncated Hilbert Transform

Author(s) -

Yangbo Ye,

Hengyong Yu,

Yuchuan Wei,

Ge Wang

Publication year - 2007

Publication title -

international journal of biomedical imaging

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.626

H-Index - 41

eISSN - 1687-4196

pISSN - 1687-4188

DOI - 10.1155/2007/63634

Subject(s) - correctness , computer science , projection (relational algebra) , iterative reconstruction , radon transform , hilbert transform , region of interest , object (grammar) , field (mathematics) , line (geometry) , computer vision , line integral , image (mathematics) , artificial intelligence , algorithm , mathematics , geometry , mathematical analysis , filter (signal processing) , pure mathematics , integral equation

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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