Cargando…
PhaseStain: the digital staining of label-free quantitative phase microscopy images using deep learning
Using a deep neural network, we demonstrate a digital staining technique, which we term PhaseStain, to transform the quantitative phase images (QPI) of label-free tissue sections into images that are equivalent to the brightfield microscopy images of the same samples that are histologically stained....
Autores principales: | Rivenson, Yair, Liu, Tairan, Wei, Zhensong, Zhang, Yibo, de Haan, Kevin, Ozcan, Aydogan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6363787/ https://www.ncbi.nlm.nih.gov/pubmed/30728961 http://dx.doi.org/10.1038/s41377-019-0129-y |
Ejemplares similares
-
Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue
por: Zhang, Yijie, et al.
Publicado: (2020) -
Emerging Advances to Transform Histopathology Using Virtual Staining
por: Rivenson, Yair, et al.
Publicado: (2020) -
Deep learning-based transformation of H&E stained tissues into special stains
por: de Haan, Kevin, et al.
Publicado: (2021) -
Deep learning-based super-resolution in coherent imaging systems
por: Liu, Tairan, et al.
Publicado: (2019) -
Digital staining facilitates biomedical microscopy
por: Fanous, Michael John, et al.
Publicado: (2023)