Evidence map›Paper›PMID 42265214›Full record

ArticleScientific reports2026

Adaptive filtering method for reducing signal saturation induced artifacts in X-ray dark-field tomography.

Henrik Mäkinen, Heikki Suhonen, Simo Huotari

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

3 authors.

Henrik MäkinenDepartment of Physics, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland. henrik.makinen@helsinki.fi.
Heikki SuhonenDepartment of Physics, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland.
Simo HuotariDepartment of Physics, University of Helsinki, P.O. Box 64, FI-00014, Helsinki, Finland.

Funding

Research Council of Finland 295696
6 · The paper itself

Abstract

X-ray dark-field imaging provides information of an object based on its small-angle scattering properties. Dark-field contrast originates from differences in the strength of scattering from micron and sub-micron sized structures in the object. A Talbot-Lau interferometer can be utilized for dark-field imaging with regular X-ray tubes. A known difficulty with the method arises, when the scattering is too strong, preventing the dark-field and phase retrieval to work accurately. This is similar to a strongly absorbing object in attenuation-based X-ray imaging, and causes problems in tomographic reconstruction that depends on the accuracy of the projected signal. In this article, we present an adaptive filtering approach for the dark-field and phase-contrast projections to improve the signal-to-noise ratio in image areas where the dark-field signal is close to saturation. This filtering improves the projection images markedly, and enables tomographic reconstruction even in cases where the sample contains strong scatterers.

Indexed as

Dark-fieldPhase-contrastTalbot-LauTomographyX-ray imaging

Identifiers

PMID42265214
PMCPMC13494008

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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.