Evidence map›Paper›PMID 28339107›Full record

ArticleMedical physics2017

Studies of signal estimation bias in grating-based x-ray multicontrast imaging.

Xu Ji, Yongshuai Ge, Ran Zhang, Ke Li, Guang-Hong Chen

Abstract read
In one paragraph

Article in Medical physics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Dual Energy Differential Phase Contrast CT (DE-DPC-CT) Imaging.IEEE transactions on medical imaging · 2020
    Article
  3. Article
  4. Impact of the sensitivity factor on the signal-to-noise ratio in grating-based phase contrast imaging.Proceedings of SPIE--the International Society for Optical Engineering · 2019
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Xu JiDepartment of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Yongshuai GeDepartment of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Ran ZhangDepartment of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Ke LiDepartment of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.
Guang-Hong ChenDepartment of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA.

Funding

Multi-Contrast X-ray Breast ImagingR01EB020521 · NIBIB · UNIVERSITY OF WISCONSIN-MADISON · PI CHEN, GUANG-HONG, LI, KE · 2016 to 2020
$2.0M
NIBIB NIH HHS R01 EB020521
6 · The paper itself

Abstract

purposeIn grating-based x-ray multi-contrast imaging, signals of three contrast mechanisms-absorption contrast, differential phase contrast (DPC), and dark-field contrast-can be estimated from the same set of acquired data. The estimated signals, N

methodsThe biases of the extracted signals (i.e., N

resultsBoth theoretical and experimental studies showed the following results: (1) The bias of signal estimation for the absorption contrast signal is zero; (2) The bias of signal estimation for N

conclusionsIn grating-based x-ray multi-contrast imaging, the estimated absorption contrast signal is unbiased; the estimated dark-field contrast signal is biased, but the relative bias is only dependent on the mean fringe visibility of the interferometer and the exposure level. The estimated DPC signal may be biased, and the bias level depends on the mean signal level, the exposure level, and the interferometer performance.

Indexed as

RadiographyData Interpretation, StatisticalX-Rayssignal biasx-ray dark-field contrast imagingx-ray imagingx-ray phase-contrast imaging

Identifiers

PMID28339107
PMCPMC6261444

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.