Incorporating the image formation process into deep learning improves network performance

We present Richardson–Lucy network (RLN), a fast and lightweight deep learning method for three-dimensional fluorescence microscopy deconvolution. RLN combines the traditional Richardson–Lucy iteration with a fully convolutional network structure, establishing a connection to the image formation pro...

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Detalles Bibliográficos
Autores principales: Li, Yue, Su, Yijun, Guo, Min, Han, Xiaofei, Liu, Jiamin, Vishwasrao, Harshad D., Li, Xuesong, Christensen, Ryan, Sengupta, Titas, Moyle, Mark W., Rey-Suarez, Ivan, Chen, Jiji, Upadhyaya, Arpita, Usdin, Ted B., Colón-Ramos, Daniel Alfonso, Liu, Huafeng, Wu, Yicong, Shroff, Hari
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636023/
https://www.ncbi.nlm.nih.gov/pubmed/36316563
http://dx.doi.org/10.1038/s41592-022-01652-7

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636023/
https://www.ncbi.nlm.nih.gov/pubmed/36316563
http://dx.doi.org/10.1038/s41592-022-01652-7

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