Evidence map›Paper›PMID 36576380›Full record

ArticleDevelopment, growth & differentiation2023

An ImageJ-based tool for three-dimensional registration between different types of microscopic images.

Hiroshi Koyama, Kanae Kishi, Seiya Mikoshiba, Toshihiko Fujimori

Abstract read
In one paragraph

Article in Development, growth & differentiation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

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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

1 citing paper in PubMed.

  1. 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

4 authors.

Hiroshi KoyamaDivision of Embryology, National Institute for Basic Biology, Okazaki, Japan.ORCID https://orcid.org/0000-0002-1217-6754
Kanae KishiDivision of Embryology, National Institute for Basic Biology, Okazaki, Japan.ORCID https://orcid.org/0000-0003-3998-9314
Seiya MikoshibaDivision of Embryology, National Institute for Basic Biology, Okazaki, Japan.
Toshihiko FujimoriDivision of Embryology, National Institute for Basic Biology, Okazaki, Japan.ORCID https://orcid.org/0000-0001-5200-4634

Funding

Japan Ministry of Education, Culture, Sports, Science and Technology Grant-in-Aid for Scientific Research on Innovative Areas "Cross-talk between moving cells and microenvironment as a basis of emerging order"Japan Science and Technology Agency, Core Research for Evolutional Science and Technology (JST-CREST) grant JPMJCR1654Japan Society for the Promotion of Science (JSPS) Grant-in-Aid for Young Scientists (B) 17K15131
6 · The paper itself

Abstract

Three-dimensional (3D) registration (i.e., alignment) between two microscopic images is very helpful to study tissues that do not adhere to substrates, such as mouse embryos and organoids, which are often 3D rotated during imaging. However, there is no 3D registration tool easily accessible for experimental biologists. Here we developed an ImageJ-based tool which allows for 3D registration accompanied with both quantitative evaluation of the accuracy and reconstruction of 3D rotated images. In this tool, several landmarks are manually provided in two images to be aligned, and 3D rotation is computed so that the distances between the paired landmarks from the two images are minimized. By simultaneously providing multiple points (e.g., all nuclei in the regions of interest) other than the landmarks in the two images, the correspondence of each point between the two images, i.e., to which nucleus in one image a certain nucleus in another image corresponds, is quantitatively explored. Furthermore, 3D rotation is applied to one of the two images, resulting in reconstruction of 3D rotated images. We demonstrated that this tool successfully achieved 3D registration and reconstruction of images in mouse pre- and post-implantation embryos, where one image was obtained during live imaging and another image was obtained from fixed embryos after live imaging. This approach provides a versatile tool applicable for various tissues and species.

Indexed as

Cell NucleusImaging, Three-DimensionalAlgorithmsAnimalsMiceImageJimage registrationmouse early embryothree-dimensional image rotation

Identifiers

PMID36576380
PMCPMC10107647

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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.