Evidence map›Paper›PMID 38786552›Full record

ArticleJournal of imaging2024

Derivative-Free Iterative One-Step Reconstruction for Multispectral CT.

Thomas Prohaszka, Lukas Neumann, Markus Haltmeier

Abstract read
In one paragraph

Article in Journal of imaging, 2024. 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

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

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.

Thomas ProhaszkaInstitute of Basic Sciences in Engineering Science, University of Innsbruck, Technikerstrasse 13, 6020 Innsbruck, Austria.
Lukas NeumannInstitute of Basic Sciences in Engineering Science, University of Innsbruck, Technikerstrasse 13, 6020 Innsbruck, Austria.ORCID 0000-0003-3263-5724
Markus HaltmeierDepartment of Mathematics, University of Innsbruck Technikerstrasse 13, 6020 Innsbruck, Austria.ORCID 0000-0001-5715-0331

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Image reconstruction in multispectral computed tomography (MSCT) requires solving a challenging nonlinear inverse problem, commonly tackled via iterative optimization algorithms. Existing methods necessitate computing the derivative of the forward map and potentially its regularized inverse. In this work, we present a simple yet highly effective algorithm for MSCT image reconstruction, utilizing iterative update mechanisms that leverage the full forward model in the forward step and a derivative-free adjoint problem. Our approach demonstrates both fast convergence and superior performance compared to existing algorithms, making it an interesting candidate for future work. We also discuss further generalizations of our method and its combination with additional regularization and other data discrepancy terms.

Indexed as

coupled physics problemsderivative-free iteratzionsinverse problemsmultispectral CT

Identifiers

PMID38786552
PMCPMC11122087

What OpenQuestion holds

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Registered trials

None linked

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.