Evidence map›Paper›PMID 42165834›Full record

ReviewRecent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer2026

Non-invasive Imaging Techniques: From Histology to In-vivo Imaging.

Elena Corbetta, Anja Silge, Hyeonsoo Bae, Marko Rodewald, Fisseha Bekele Legesse, Tobias Meyer, Jürgen Popp, Thomas Bocklitz

Abstract readReview
PubMed Publisher
In one paragraph

Review in Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer, 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

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

8 authors.

Elena CorbettaResearch Department of Photonic Data Science, Leibniz Institute of Photonic Technology, Jena, Germany.
Anja SilgeInstitute of Physical Chemistry (IPC), Friedrich Schiller University Jena, Jena, Germany.
Hyeonsoo BaeInstitute of Physical Chemistry (IPC), Friedrich Schiller University Jena, Jena, Germany.
Marko RodewaldInstitute of Physical Chemistry (IPC), Friedrich Schiller University Jena, Jena, Germany.
Fisseha Bekele LegesseInstitute of Physical Chemistry (IPC), Friedrich Schiller University Jena, Jena, Germany.
Tobias MeyerInstitute of Physical Chemistry (IPC), Friedrich Schiller University Jena, Jena, Germany.
Jürgen PoppInstitute of Physical Chemistry (IPC) and Abbe Center of Photonics (ACP), Friedrich Schiller University Jena, Jena, Germany.
Thomas BocklitzResearch Department of Photonic Data Science, Leibniz Institute of Photonic Technology, Jena, Germany. thomas.bocklitz@uni-jena.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this chapter we introduce and review molecular sensitive imaging techniques that bridge the gap between ex-vivo and in-vivo analysis. In detail, we describe spontaneous Raman spectral imaging, coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), second harmonic generation (SHG), third harmonic generation (THG), two-photon excited fluorescence (TPEF) and fluorescence lifetime imaging (FLIM). After reviewing these imaging techniques, we briefly introduce the chemometric and machine learning methods required to use these imaging techniques in diagnostic applications.

Indexed as

Molecular ImagingNeoplasmsAnimalsHumansOptical ImagingSpectrum Analysis, RamanChemometricsCoherent anti-Stokes Raman scattering (CARS)Fluorescence lifetime imaging (FLIM)Machine learningNon-invasive imagingRaman spectral imagingSecond harmonic generation (SHG)Stimulated Raman scattering (SRS)Third harmonic generation (THG)Two-photon excited fluorescence (TPEF)

Identifiers

PMID42165834

What OpenQuestion holds

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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.