Evidence map›Paper›PMID 28392451›Full record

ArticleJournal of structural biology2017

Electron tomography simulator with realistic 3D phantom for evaluation of acquisition, alignment and reconstruction methods.

Xiaohua Wan, Tsvi Katchalski, Christopher Churas, Sreya Ghosh, Sebastien Phan, Albert Lawrence, Yu Hao, Ziying Zhou, Ruijuan Chen, Yu Chen and 2 more

Abstract read
In one paragraph

Article in Journal of structural biology, 2017. 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

12 authors.

Xiaohua WanInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China; National Center for Microscopy and Imaging Research, University of California, San Diego, USA.
Tsvi KatchalskiNational Center for Microscopy and Imaging Research, University of California, San Diego, USA.
Christopher ChurasNational Center for Microscopy and Imaging Research, University of California, San Diego, USA.
Sreya GhoshNational Center for Microscopy and Imaging Research, University of California, San Diego, USA.
Sebastien PhanNational Center for Microscopy and Imaging Research, University of California, San Diego, USA.
Albert LawrenceNational Center for Microscopy and Imaging Research, University of California, San Diego, USA. Electronic address: albert.rick.lawrence@gmail.com.
Yu HaoInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Ziying ZhouInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China; Beijing Institute of Technology, Beijing, China.
Ruijuan ChenSchool of Electronic and Information Engineering, Tianjin Polytechnic University, Tianjin, China; National Center for Microscopy and Imaging Research, University of California, San Diego, USA.
Yu ChenInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Fa ZhangInstitute of Computing Technology, Chinese Academy of Sciences, Beijing, China.
Mark H EllismanNational Center for Microscopy and Imaging Research, University of California, San Diego, USA; Departments of Neurosciences and Bioengineering, University of California, San Diego, USA.

Funding

IVEM and Image Analysis ResourceP41GM103412 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ELLISMAN, MARK H · 2012 to 2019
$17.9M
NIGMS NIH HHS P41 GM103412
6 · The paper itself

Abstract

Because of the significance of electron microscope tomography in the investigation of biological structure at nanometer scales, ongoing improvement efforts have been continuous over recent years. This is particularly true in the case of software developments. Nevertheless, verification of improvements delivered by new algorithms and software remains difficult. Current analysis tools do not provide adaptable and consistent methods for quality assessment. This is particularly true with images of biological samples, due to image complexity, variability, low contrast and noise. We report an electron tomography (ET) simulator with accurate ray optics modeling of image formation that includes curvilinear trajectories through the sample, warping of the sample and noise. As a demonstration of the utility of our approach, we have concentrated on providing verification of the class of reconstruction methods applicable to wide field images of stained plastic-embedded samples. Accordingly, we have also constructed digital phantoms derived from serial block face scanning electron microscope images. These phantoms are also easily modified to include alignment features to test alignment algorithms. The combination of more realistic phantoms with more faithful simulations facilitates objective comparison of acquisition parameters, alignment and reconstruction algorithms and their range of applicability. With proper phantoms, this approach can also be modified to include more complex optical models, including distance-dependent blurring and phase contrast functions, such as may occur in cryotomography.

Indexed as

AlgorithmsElectron Microscope TomographyImage Processing, Computer-AssistedPhantoms, ImagingSoftwareAlignmentBlock faceCurvilinearElectronInversionMicroscopeReconstructionSeriesSimulatorTiltTomographyTrackingWarping

Identifiers

PMID28392451
PMCPMC5773259

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.