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2022-01-10

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cc-by (c) Klatzow, James et al., 2022
Si us plau utilitzeu sempre aquest identificador per citar o enllaçar aquest document: https://hdl.handle.net/2445/194747

µMatch: 3D shape correspondence for biological image data

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Recurs relacionat

https://doi.org/10.3389/fcomp.2022.777615

Resum

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.

Matèries

Visualització tridimensional, Impressió 3D, Python (Llenguatge de programació), Biotecnologia

Matèries (anglès)

Three-dimensional display systems, Three-dimensional printing, Python (Computer program language), Biotechnology

Citació

Col·leccions

Articles publicats en revistes (Biologia Evolutiva, Ecologia i Ciències Ambientals)

Citació

KLATZOW, James, et al. µMatch: 3D shape correspondence for biological image data. Frontiers in Computer Science. 2022. Vol. 4. ISSN 2624-9898. [consulted: 17 of August of 2026]. Available at: https://hdl.handle.net/2445/194747

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