Evidence map›Paper›PMID 33024955›Full record

ArticleJournal of structural biology: X2020

Improvements on marker-free images alignment for electron tomography.

C O S Sorzano, F de Isidro-Gómez, E Fernández-Giménez, D Herreros, S Marco, J M Carazo, C Messaoudi

Abstract read
In one paragraph

Article in Journal of structural biology: X, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 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

7 authors.

C O S SorzanoBiocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain.
F de Isidro-GómezBiocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain.
E Fernández-GiménezBiocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain.
D HerrerosBiocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain.
S MarcoInstitite Curie, 110 Avenue de Bures, 91440 Bures-sur-Yvette, France.
J M CarazoBiocomputing Unit, National Center for Biotechnology (CSIC), c/Darwin, 3, Campus Universidad Aut'onoma, 28049 Cantoblanco, Madrid, Spain.
C MessaoudiInstitite Curie, 110 Avenue de Bures, 91440 Bures-sur-Yvette, France.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Electron tomography is a technique to obtain three-dimensional structural information of samples. However, the technique is limited by shifts occurring during acquisition that need to be corrected before the reconstruction process. In 2009, we proposed an approach for post-acquisition alignment of tilt series images. This approach was marker-free, based on patch tracking and integrated in free software. Here, we present improvements to the method to make it more reliable, stable and accurate. In addition, we modified the image formation model underlying the alignment procedure to include different deformations occurring during acquisition. We propose a new way to correct these computed deformations to obtain reconstructions with reduced artifacts. The new approach has demonstrated to improve the quality of the final 3D reconstruction, giving access to better defined structures for different transmission electron tomography methods: resin embedded STEM-tomography and cryo-TEM tomography. The method is freely available in TomoJ software.

Indexed as

Electron tomographyImage processingTilt series alignment

Identifiers

PMID33024955
PMCPMC7527754

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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.