Evidence map›Paper›PMID 40106510›Full record

ArticlePloS one2025

Automated sample tracking and parameter adaption for scanning laser optical tomography.

Hannes Benecke, Firas Almadani, Johannes Heske, Tobias May, Ludger Overmeyer, Sonja Johannsmeier, Tammo Ripken

Abstract read
In one paragraph

Article in PloS one, 2025. 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

7 authors.

Hannes BeneckeLife Sciences Department, Laser Zentrum Hannover e.V, Hannover, Germany.ORCID https://orcid.org/0000-0002-7803-1304
Firas AlmadaniLife Sciences Department, Laser Zentrum Hannover e.V, Hannover, Germany.
Johannes HeskeLife Sciences Department, Laser Zentrum Hannover e.V, Hannover, Germany.
Tobias MayInSCREENeX GmbH, Braunschweig, Germany.
Ludger OvermeyerInstitute of Transport and Automation Technology, An der Universität, Garbsen, Germany.
Sonja JohannsmeierLife Sciences Department, Laser Zentrum Hannover e.V, Hannover, Germany.
Tammo RipkenLife Sciences Department, Laser Zentrum Hannover e.V, Hannover, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-destructive, three-dimensional imaging techniques are of great importance in medicine as well as in technical analysis. In this context, it is of particular importance to generate reliable and repeatable results of high quality. This can be aided by automation of manual processes. One of these imaging techniques, the Scanning Laser Optical Tomography, currently requires manual sample alignment by the user to achieve the highest possible image quality. This alignment demands skillful hand-eye coordination as well as experience on the part of the user, and thus often leads to inconsistent imaging results. To overcome this problem, this paper presents a technique for software-based automation of this challenge. The sample is not physically aligned, but digitally detected and tracked during the acquisition. Residual motion artifacts that interfere with tomographic reconstruction are corrected using a second automation algorithm. The combination of the two new algorithms significantly improves the quality of imaging and also increases the reliability and degree of automation of the system, making it accessible to a wide range of users.

Indexed as

LasersTomography, OpticalAlgorithmsArtifactsAutomationHumansImage Processing, Computer-AssistedImaging, Three-DimensionalReproducibility of ResultsSoftware

Identifiers

PMID40106510
PMCPMC11922203

What OpenQuestion holds

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LicenceCC BY
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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.