µMatch: 3D shape correspondence for biological image data

Modern microscopy technologies allow imaging biological objects in 3D over a wide range of spatial and temporal scales, opening the way for a quantitative assessment of morphology. However, establishing a correspondence between objects to be compared, a first necessary step of most shape analysis wo...

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Detalles Bibliográficos
Autores: Klatzow, James, Dalmasso, Giovanni, Martínez Abadías, Neus, 1978-, Sharpe, James, Uhlmann, Virginie
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Institución:Universidad de Barcelona
Repositorio:Dipòsit Digital de la UB
OAI Identifier:oai:diposit.ub.edu:2445/194747
Acceso en línea:https://hdl.handle.net/2445/194747
Access Level:acceso abierto
Palabra clave:Visualització tridimensional
Impressió 3D
Python (Llenguatge de programació)
Biotecnologia
Three-dimensional display systems
Three-dimensional printing
Python (Computer program language)
Biotechnology
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spelling µMatch: 3D shape correspondence for biological image dataKlatzow, JamesDalmasso, GiovanniMartínez Abadías, Neus, 1978-Sharpe, JamesUhlmann, VirginieVisualització tridimensionalImpressió 3DPython (Llenguatge de programació)BiotecnologiaThree-dimensional display systemsThree-dimensional printingPython (Computer program language)BiotechnologyModern microscopy technologies allow imaging biological objects in 3D over a wide range of spatial and temporal scales, opening the way for a quantitative assessment of morphology. However, establishing a correspondence between objects to be compared, a first necessary step of most shape analysis workflows, remains challenging for soft-tissue objects without striking features allowing them to be landmarked. To address this issue, we introduce the μMatch 3D shape correspondence pipeline. μMatch implements a state-of-the-art correspondence algorithm initially developed for computer graphics and packages it in a streamlined pipeline including tools to carry out all steps from input data pre-processing to classical shape analysis routines. Importantly, μMatch does not require any landmarks on the object surface and establishes correspondence in a fully automated manner. Our open-source method is implemented in Python and can be used to process collections of objects described as triangular meshes. We quantitatively assess the validity of μMatch relying on a well-known benchmark dataset and further demonstrate its reliability by reproducing published results previously obtained through manual landmarking.Frontiers Media2022info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://hdl.handle.net/2445/194747Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)reponame:Dipòsit Digital de la UBinstname:Universidad de BarcelonaInglésReproducció del document publicat a: https://doi.org/10.3389/fcomp.2022.777615Frontiers in Computer Science, 2022, vol. 4https://doi.org/10.3389/fcomp.2022.777615cc-by (c) Klatzow, James et al., 2022https://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:diposit.ub.edu:2445/1947472026-05-27T06:46:51Z
dc.title.none.fl_str_mv µMatch: 3D shape correspondence for biological image data
title µMatch: 3D shape correspondence for biological image data
spellingShingle µMatch: 3D shape correspondence for biological image data
Klatzow, James
Visualització tridimensional
Impressió 3D
Python (Llenguatge de programació)
Biotecnologia
Three-dimensional display systems
Three-dimensional printing
Python (Computer program language)
Biotechnology
title_short µMatch: 3D shape correspondence for biological image data
title_full µMatch: 3D shape correspondence for biological image data
title_fullStr µMatch: 3D shape correspondence for biological image data
title_full_unstemmed µMatch: 3D shape correspondence for biological image data
title_sort µMatch: 3D shape correspondence for biological image data
dc.creator.none.fl_str_mv Klatzow, James
Dalmasso, Giovanni
Martínez Abadías, Neus, 1978-
Sharpe, James
Uhlmann, Virginie
author Klatzow, James
author_facet Klatzow, James
Dalmasso, Giovanni
Martínez Abadías, Neus, 1978-
Sharpe, James
Uhlmann, Virginie
author_role author
author2 Dalmasso, Giovanni
Martínez Abadías, Neus, 1978-
Sharpe, James
Uhlmann, Virginie
author2_role author
author
author
author
dc.subject.none.fl_str_mv Visualització tridimensional
Impressió 3D
Python (Llenguatge de programació)
Biotecnologia
Three-dimensional display systems
Three-dimensional printing
Python (Computer program language)
Biotechnology
topic Visualització tridimensional
Impressió 3D
Python (Llenguatge de programació)
Biotecnologia
Three-dimensional display systems
Three-dimensional printing
Python (Computer program language)
Biotechnology
description Modern microscopy technologies allow imaging biological objects in 3D over a wide range of spatial and temporal scales, opening the way for a quantitative assessment of morphology. However, establishing a correspondence between objects to be compared, a first necessary step of most shape analysis workflows, remains challenging for soft-tissue objects without striking features allowing them to be landmarked. To address this issue, we introduce the μMatch 3D shape correspondence pipeline. μMatch implements a state-of-the-art correspondence algorithm initially developed for computer graphics and packages it in a streamlined pipeline including tools to carry out all steps from input data pre-processing to classical shape analysis routines. Importantly, μMatch does not require any landmarks on the object surface and establishes correspondence in a fully automated manner. Our open-source method is implemented in Python and can be used to process collections of objects described as triangular meshes. We quantitatively assess the validity of μMatch relying on a well-known benchmark dataset and further demonstrate its reliability by reproducing published results previously obtained through manual landmarking.
publishDate 2022
dc.date.none.fl_str_mv 2022
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/194747
url https://hdl.handle.net/2445/194747
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.3389/fcomp.2022.777615
Frontiers in Computer Science, 2022, vol. 4
https://doi.org/10.3389/fcomp.2022.777615
dc.rights.none.fl_str_mv cc-by (c) Klatzow, James et al., 2022
https://creativecommons.org/licenses/by/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by (c) Klatzow, James et al., 2022
https://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Frontiers Media
publisher.none.fl_str_mv Frontiers Media
dc.source.none.fl_str_mv Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)
reponame:Dipòsit Digital de la UB
instname:Universidad de Barcelona
instname_str Universidad de Barcelona
reponame_str Dipòsit Digital de la UB
collection Dipòsit Digital de la UB
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,301629

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