Evidence map›Paper›PMID 28133404›Full record

ArticleMathematical methods in the applied sciences2017

Inverse problems of combined photoacoustic and optical coherence tomography.

Peter Elbau, Leonidas Mindrinos, Otmar Scherzer

Abstract read
In one paragraph

Article in Mathematical methods in the applied sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Inverse problems of combined photoacoustic and optical coherence tomography.Mathematical methods in the applied sciences · 2017
    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

3 authors.

Peter ElbauComputational Science Center University of Vienna Oskar-Morgenstern-Platz 1 Vienna A-1090 Austria.
Leonidas MindrinosComputational Science Center University of Vienna Oskar-Morgenstern-Platz 1 Vienna A-1090 Austria.
Otmar ScherzerComputational Science Center University of Vienna Oskar-Morgenstern-Platz 1 Vienna A-1090 Austria; Johann Radon Institute for Computational and Applied Mathematics (RICAM) Altenbergerstraße 69 Linz A-4040 Austria.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Optical coherence tomography (OCT) and photoacoustic tomography are emerging non-invasive biological and medical imaging techniques. It is a recent trend in experimental science to design experiments that perform photoacoustic tomography and OCT imaging at once. In this paper, we present a mathematical model describing the dual experiment. Because OCT is mathematically modelled by Maxwell's equations or some simplifications of it, whereas the light propagation in quantitative photoacoustics is modelled by (simplifications of) the radiative transfer equation, the first step in the derivation of a mathematical model of the dual experiment is to obtain a unified mathematical description, which in our case are Maxwell's equations. As a by-product, we therefore derive a new mathematical model of photoacoustic tomography based on Maxwell's equations. It is well known by now that without additional assumptions on the medium, it is not possible to uniquely reconstruct all optical parameters from either one of these modalities alone. We show that in the combined approach, one has additional information, compared with a single modality, and the inverse problem of reconstruction of the optical parameters becomes feasible. © 2016 The Authors.

Indexed as

hybrid imagingoptical coherence tomographyquantitative photoacoustic tomography

Identifiers

PMID28133404
PMCPMC5242291

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.