A deep learning method to map tissue architecture

A new study in Nature Methods describes a computational method named UTAG (unsupervised discovery of tissue architecture with graphs) that aims to identify and quantify higher-level tissue domains from biological images without previous knowledge.

Detalles Bibliográficos
Autor principal: Koch, Linda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Research Highlight
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9735151/
https://www.ncbi.nlm.nih.gov/pubmed/36473953
http://dx.doi.org/10.1038/s41576-022-00564-8
Descripción
Sumario:A new study in Nature Methods describes a computational method named UTAG (unsupervised discovery of tissue architecture with graphs) that aims to identify and quantify higher-level tissue domains from biological images without previous knowledge.

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