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Chord‐based image reconstruction in cone‐beam CT with a curved detector
Author(s) -
Zuo Nianming,
Xia Dan,
Zou Yu,
Jiang Tianzi,
Pan XiaoChuan
Publication year - 2006
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.2337270
Subject(s) - chord (peer to peer) , detector , iterative reconstruction , scanner , algorithm , computer science , computer vision , optics , image resolution , tomography , artificial intelligence , physics , distributed computing
Modern computed tomography (CT) scanners use cone‐beam configurations for increasing volume coverage, improving x‐ray‐tube utilization, and yielding isotropic spatial resolution. Recently, there have been significant developments in theory and algorithms for exact image reconstruction from cone‐beam projections. In particular, algorithms have been proposed for image reconstruction on chords; and advantages over the existing algorithms offered by the chord‐based algorithms include the high flexibility of exact image reconstruction for general scanning trajectories and the capability of exact reconstruction of images within a region of interest from truncated data. These chord‐based algorithms have been developed only for flat‐panel detectors. Many cone‐beam CT scanners employ curved detectors for important practical considerations. Therefore, in this work, we have derived chord‐based algorithms for a curved detector so that they can be applied to reconstructing images directly from data acquired by use of a CT scanner with a curved detector. We have also conducted preliminary numerical studies to demonstrate and evaluate the reconstruction properties of the derived chord‐based algorithms for curved detectors.