Evidence map›Paper›PMID 27646194›Full record

ArticleScientific reports2016

Biological application of Compressed Sensing Tomography in the Scanning Electron Microscope.

Matteo Ferroni, Alberto Signoroni, Andrea Sanzogni, Luca Masini, Andrea Migliori, Luca Ortolani, Alessandro Pezza, Vittorio Morandi

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. 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
2.5field-weighted citation impact, top 9% of its field
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, 12 citations in OpenAlex.

  1. Review
  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

8 authors at 2 institutions in 1 country.

Matteo FerroniBrescia University, Dept. of Information Engineering, Via Branze, 25123 Brescia, Italy.
Alberto SignoroniBrescia University, Dept. of Information Engineering, Via Branze, 25123 Brescia, Italy.
Andrea SanzogniBrescia University, Dept. of Information Engineering, Via Branze, 25123 Brescia, Italy.
Luca MasiniCNR - Microelectronic and Microsystems Institute, via Gobetti 101, 40129 Bologna, Italy.
Andrea MiglioriCNR - Microelectronic and Microsystems Institute, via Gobetti 101, 40129 Bologna, Italy.
Luca OrtolaniCNR - Microelectronic and Microsystems Institute, via Gobetti 101, 40129 Bologna, Italy.
Alessandro PezzaCNR - Microelectronic and Microsystems Institute, via Gobetti 101, 40129 Bologna, Italy.
Vittorio MorandiCNR - Microelectronic and Microsystems Institute, via Gobetti 101, 40129 Bologna, Italy.
Institute for Microelectronics and Microsystems · ITUniversity of Brescia · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The three-dimensional tomographic reconstruction of a biological sample, namely collagen fibrils in human dermal tissue, was obtained from a set of projection-images acquired in the Scanning Electron Microscope. A tailored strategy for the transmission imaging mode was implemented in the microscope and proved effective in acquiring the projections needed for the tomographic reconstruction. Suitable projection alignment and Compressed Sensing formulation were used to overcome the limitations arising from the experimental acquisition strategy and to improve the reconstruction of the sample. The undetermined problem of structure reconstruction from a set of projections, limited in number and angular range, was indeed supported by exploiting the sparsity of the object projected in the electron microscopy images. In particular, the proposed system was able to preserve the reconstruction accuracy even in presence of a significant reduction of experimental projections.

Identifiers

PMID27646194
PMCPMC5028842
OpenAlexW2522622651

What OpenQuestion holds

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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.