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http://hdl.handle.net/2445/194747
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DC Field | Value | Language |
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dc.contributor.author | Klatzow, James | - |
dc.contributor.author | Dalmasso, Giovanni | - |
dc.contributor.author | Martínez Abadías, Neus, 1978- | - |
dc.contributor.author | Sharpe, James | - |
dc.contributor.author | Uhlmann, Virginie | - |
dc.date.accessioned | 2023-03-07T09:52:12Z | - |
dc.date.available | 2023-03-07T09:52:12Z | - |
dc.date.issued | 2022-01-10 | - |
dc.identifier.issn | 2624-9898 | - |
dc.identifier.uri | http://hdl.handle.net/2445/194747 | - |
dc.description.abstract | 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. | - |
dc.format.extent | 16 p. | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | eng | - |
dc.publisher | Frontiers Media | - |
dc.relation.isformatof | Reproducció del document publicat a: https://doi.org/10.3389/fcomp.2022.777615 | - |
dc.relation.ispartof | Frontiers in Computer Science, 2022, vol. 4 | - |
dc.relation.uri | https://doi.org/10.3389/fcomp.2022.777615 | - |
dc.rights | cc-by (c) Klatzow, James et al., 2022 | - |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | - |
dc.source | Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals) | - |
dc.subject.classification | Visualització tridimensional | - |
dc.subject.classification | Impressió 3D | - |
dc.subject.classification | Python (Llenguatge de programació) | - |
dc.subject.classification | Biotecnologia | - |
dc.subject.other | Three-dimensional display systems | - |
dc.subject.other | Three-dimensional printing | - |
dc.subject.other | Python (Computer program language) | - |
dc.subject.other | Biotechnology | - |
dc.title | µMatch: 3D shape correspondence for biological image data | - |
dc.type | info:eu-repo/semantics/article | - |
dc.type | info:eu-repo/semantics/publishedVersion | - |
dc.identifier.idgrec | 717380 | - |
dc.date.updated | 2023-03-07T09:52:12Z | - |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | - |
Appears in Collections: | Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals) |
Files in This Item:
File | Description | Size | Format | |
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717380.pdf | 5.01 MB | Adobe PDF | View/Open |
This item is licensed under a Creative Commons License