Evidence map›Paper›PMID 35200730›Full record

ArticleJournal of imaging2022

A Priori Information Based Time-Resolved 3D Analysis of the Trajectory and Spatial Orientation of Fast-Moving Objects Using High-Speed Flash X-ray Imaging.

Ralph Langkemper, Stefan Moser, Markus Büttner, Dominik Rakus, Axel Sättler, Siegfried Nau

Abstract read
In one paragraph

Article in Journal of imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

6 authors.

Ralph LangkemperFraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Ernst-Zermelo-Straße 4, 79104 Freiburg, Germany.
Stefan MoserFraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Ernst-Zermelo-Straße 4, 79104 Freiburg, Germany.
Markus BüttnerFraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Ernst-Zermelo-Straße 4, 79104 Freiburg, Germany.
Dominik RakusFraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Ernst-Zermelo-Straße 4, 79104 Freiburg, Germany.
Axel SättlerFraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Ernst-Zermelo-Straße 4, 79104 Freiburg, Germany.ORCID 0000-0001-5501-6083
Siegfried NauFraunhofer Institute for High-Speed Dynamics, Ernst-Mach-Institut, EMI, Ernst-Zermelo-Straße 4, 79104 Freiburg, Germany.ORCID 0000-0002-2261-9029

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper shows that the X-ray analysis method known from the medical field, using a priori information, can provide a lot more information than the common analysis for high-speed experiments. Via spatial registration of known 3D shapes with the help of 2D X-ray images, it is possible to derive the spatial position and orientation of the examined parts. The method was demonstrated on the example of the sabot discard of a subcaliber projectile. The velocity of the examined object amounts up to 1600 m/s. As a priori information, the geometry of the experimental setup and the shape of the projectile and sabot parts were used. The setup includes four different positions or points in time to examine the behavior over time. It was possible to place the parts within a spatial accuracy of 0.85 mm (standard deviation), respectively 1.7 mm for 95% of the errors within this range. The error is mainly influenced by the accuracy of the experimental setup and the tagging of the feature points on the X-ray images.

Indexed as

2D to 3D registrationa priori informationfast-moving objecthigh-speed X-ray imagingsabot discard

Identifiers

PMID35200730
PMCPMC8879217

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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.