Evidence map›Paper›PMID 26607812›Full record

ArticleBMC bioinformatics2015

Fully automated registration of vibrational microspectroscopic images in histologically stained tissue sections.

Chen Yang, Daniel Niedieker, Frederik Grosserüschkamp, Melanie Horn, Andrea Tannapfel, Angela Kallenbach-Thieltges, Klaus Gerwert, Axel Mosig

Abstract read
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Article in BMC bioinformatics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

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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.

Chen YangDepartment of Biophysics, CAS-MPG Partner Institute and Key Laboratory for Computational Biology, 320 Yueyang Road, Shanghai, 200031, China. yangchen@picb.ac.cn.
Daniel NiediekerDepartment of Biophysics, Ruhr-University Bochum, Universitätsstraße 150, Bochum, 44780, Germany. daniel.niedieker@bph.rub.de.
Frederik GrosserüschkampDepartment of Biophysics, Ruhr-University Bochum, Universitätsstraße 150, Bochum, 44780, Germany. fred@bph.rub.de.
Melanie HornDepartment of Biophysics, Ruhr-University Bochum, Universitätsstraße 150, Bochum, 44780, Germany. melanie.horn@bph.rub.de.
Andrea TannapfelInstitute of Pathology, Ruhr-University Bochum, Bochum, Germany, Bürkle-de-la-Camp-Platz 1, Bochum, 44789, Germany. andrea.tannapfel@rub.de.
Angela Kallenbach-ThieltgesDepartment of Biophysics, Ruhr-University Bochum, Universitätsstraße 150, Bochum, 44780, Germany. angela@bph.rub.de.
Klaus GerwertDepartment of Biophysics, CAS-MPG Partner Institute and Key Laboratory for Computational Biology, 320 Yueyang Road, Shanghai, 200031, China. gerwert@bph.rub.de.
Axel MosigDepartment of Biophysics, Ruhr-University Bochum, Universitätsstraße 150, Bochum, 44780, Germany. axel.mosig@bph.rub.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn recent years, hyperspectral microscopy techniques such as infrared or Raman microscopy have been applied successfully for diagnostic purposes. In many of the corresponding studies, it is common practice to measure one and the same sample under different types of microscopes. Any joint analysis of the two image modalities requires to overlay the images, so that identical positions in the sample are located at the same coordinate in both images. This step, commonly referred to as image registration, has typically been performed manually in the lack of established automated computational registration tools.

resultsWe propose a corresponding registration algorithm that addresses this registration problem, and demonstrate the robustness of our approach in different constellations of microscopes. First, we deal with subregion registration of Fourier Transform Infrared (FTIR) microscopic images in whole-slide histopathological staining images. Second, we register FTIR imaged cores of tissue microarrays in their histopathologically stained counterparts, and finally perform registration of Coherent anti-Stokes Raman spectroscopic (CARS) images within histopathological staining images.

conclusionsOur validation involves a large variety of samples obtained from colon, bladder, and lung tissue on three different types of microscopes, and demonstrates that our proposed method works fully automated and highly robust in different constellations of microscopes involving diverse types of tissue samples.

Indexed as

AlgorithmsPattern Recognition, AutomatedColonHumansImage Processing, Computer-AssistedLungMicroscopySpectroscopy, Fourier Transform InfraredSpectrum Analysis, RamanTissue Array AnalysisUrinary Bladder

Identifiers

PMID26607812
PMCPMC4659215

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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.