Evidence map›Paper›PMID 33921629›Full record

ArticleSensors (Basel, Switzerland)2021

Proof of Principle for Direct Reconstruction of Qualitative Depth Information from Turbid Media by a Single Hyper Spectral Image.

Martin Hohmann, Damaris Hecht, Benjamin Lengenfelder, Moritz Späth, Florian Klämpfl, Michael Schmidt

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. 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.

Martin HohmannInstitute of Photonic Technologies (LPT), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Konrad-Zuse-Strasse 3/5, 91052 Erlangen, Germany.
Damaris HechtInstitute of Photonic Technologies (LPT), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Konrad-Zuse-Strasse 3/5, 91052 Erlangen, Germany.
Benjamin LengenfelderInstitute of Photonic Technologies (LPT), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Konrad-Zuse-Strasse 3/5, 91052 Erlangen, Germany.
Moritz SpäthInstitute of Photonic Technologies (LPT), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Konrad-Zuse-Strasse 3/5, 91052 Erlangen, Germany.ORCID 0000-0002-9852-1212
Florian KlämpflInstitute of Photonic Technologies (LPT), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Konrad-Zuse-Strasse 3/5, 91052 Erlangen, Germany.
Michael SchmidtInstitute of Photonic Technologies (LPT), Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Konrad-Zuse-Strasse 3/5, 91052 Erlangen, Germany.

Funding

Deutsche Forschungsgemeinschaft 337270237
6 · The paper itself

Abstract

In medical applications, hyper-spectral imaging is becoming more and more common. It has been shown to be more effective for classification and segmentation than normal RGB imaging because narrower wavelength bands are used, providing a higher contrast. However, until now, the fact that hyper-spectral images also contain information about the three-dimensional structure of turbid media has been neglected. In this study, it is shown that it is possible to derive information about the depth of inclusions in turbid phantoms from a single hyper-spectral image. Here, the depth information is encoded by a combination of scattering and absorption within the phantom. Although scatter-dominated regions increase the backscattering for deep vessels, absorption has the opposite effect. With this argumentation, it makes sense to assume that, under certain conditions, a wavelength is not influenced by the depth of the inclusion and acts as an iso-point. This iso-point could be used to easily derive information about the depth of an inclusion. In this study, it is shown that the iso-point exists in some cases. Moreover, it is shown that the iso-point can be used to obtain precise depth information.

Indexed as

Phantoms, ImagingHSDRhyperspectralhyperspectral depth reconstructionhyperspectral imaging

Identifiers

PMID33921629
PMCPMC8073672

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.