Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy

Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisition, applying additional dose, or introducing more...

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Detalles Bibliográficos
Autores principales: Guo, Min, Wu, Yicong, Su, Yijun, Qian, Shuhao, Krueger, Eric, Christensen, Ryan, Kroeschell, Grant, Bui, Johnny, Chaw, Matthew, Zhang, Lixia, Liu, Jiamin, Hou, Xuekai, Han, Xiaofei, Ma, Xuefei, Zhovmer, Alexander, Combs, Christian, Moyle, Mark, Yemini, Eviatar, Liu, Huafeng, Liu, Zhiyi, La Riviere, Patrick, Colón-Ramos, Daniel, Shroff, Hari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659418/
https://www.ncbi.nlm.nih.gov/pubmed/37986950
http://dx.doi.org/10.1101/2023.10.15.562439

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10659418/
https://www.ncbi.nlm.nih.gov/pubmed/37986950
http://dx.doi.org/10.1101/2023.10.15.562439

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