ArticleVisual computing for industry, biomedicine, and art2020
Analytic time-of-flight positron emission tomography reconstruction: three-dimensional case.
Article in Visual computing for industry, biomedicine, and art, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
2 citing papers in PubMed.
- Development of an optically emulated computed tomography scanner for college education.Visual computing for industry, biomedicine, and art · 2026Article
- Poisson-noise weighted filter for time-of-flight positron emission tomography.Visual computing for industry, biomedicine, and art · 2020Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
In a positron emission tomography (PET) scanner, the time-of-flight (TOF) information gives us rough event position along the line-of-response (LOR). Using the TOF information for PET image reconstruction is able to reduce image noise. The state-of-the-art TOF PET image reconstruction uses iterative algorithms. This study introduces an analytic TOF PET algorithm that focuses on three-dimensional (3D) reconstruction. The proposed algorithm is in the form of backprojection filtering, in which the backprojection is performed first by using a time-resolution profile function, and then a 3D filter is applied to the backprojected image. For the list-mode data, the backprojection is carried out in the event-by-event fashion, and the timing resolution determined weighting function is used along the projection LOR. Computer simulations are carried out to verify the feasibility of the proposed algorithm.
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Registered trials
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