Artikel ; Online: μMatch
Frontiers in Computer Science, Vol
3D Shape Correspondence for Biological Image Data
2022 Band 4
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 ... ...
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. |
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Schlagwörter | bioimage analysis ; shape quantification ; correspondence ; alignment ; computational morphometry ; Electronic computers. Computer science ; QA75.5-76.95 |
Thema/Rubrik (Code) | 004 |
Sprache | Englisch |
Erscheinungsdatum | 2022-02-01T00:00:00Z |
Verlag | Frontiers Media S.A. |
Dokumenttyp | Artikel ; Online |
Datenquelle | BASE - Bielefeld Academic Search Engine (Lebenswissenschaftliche Auswahl) |
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