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Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks

Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many...

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Detalles Bibliográficos
Autores principales: Grocott, Timothy, Thomas, Paul, Münsterberg, Andrea E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749973/
https://www.ncbi.nlm.nih.gov/pubmed/26864723
http://dx.doi.org/10.1038/srep20732
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author Grocott, Timothy
Thomas, Paul
Münsterberg, Andrea E.
author_facet Grocott, Timothy
Thomas, Paul
Münsterberg, Andrea E.
author_sort Grocott, Timothy
collection PubMed
description Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states.
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spelling pubmed-47499732016-02-17 Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks Grocott, Timothy Thomas, Paul Münsterberg, Andrea E. Sci Rep Article Image registration is a gateway technology for Developmental Systems Biology, enabling computational analysis of related datasets within a shared coordinate system. Many registration tools rely on landmarks to ensure that datasets are correctly aligned; yet suitable landmarks are not present in many datasets. Atlas Toolkit is a Fiji/ImageJ plugin collection offering elastic group-wise registration of 3D morphological datasets, guided by segmentation of the interesting morphology. We demonstrate the method by combinatorial mapping of cell signalling events in the developing eyes of chick embryos, and use the integrated datasets to predictively enumerate Gene Regulatory Network states. Nature Publishing Group 2016-02-11 /pmc/articles/PMC4749973/ /pubmed/26864723 http://dx.doi.org/10.1038/srep20732 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Grocott, Timothy
Thomas, Paul
Münsterberg, Andrea E.
Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks
title Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks
title_full Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks
title_fullStr Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks
title_full_unstemmed Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks
title_short Atlas Toolkit: Fast registration of 3D morphological datasets in the absence of landmarks
title_sort atlas toolkit: fast registration of 3d morphological datasets in the absence of landmarks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4749973/
https://www.ncbi.nlm.nih.gov/pubmed/26864723
http://dx.doi.org/10.1038/srep20732
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