TDAExplore: Quantitative analysis of fluorescence microscopy images through topology-based machine learning

Recent advances in machine learning have greatly enhanced automatic methods to extract information from fluorescence microscopy data. However, current machine-learning-based models can require hundreds to thousands of images to train, and the most readily accessible models classify images without de...

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Detalles Bibliográficos
Autores principales: Edwards, Parker, Skruber, Kristen, Milićević, Nikola, Heidings, James B., Read, Tracy-Ann, Bubenik, Peter, Vitriol, Eric A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600226/
https://www.ncbi.nlm.nih.gov/pubmed/34820649
http://dx.doi.org/10.1016/j.patter.2021.100367

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600226/
https://www.ncbi.nlm.nih.gov/pubmed/34820649
http://dx.doi.org/10.1016/j.patter.2021.100367

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