Cargando…
Deep learning enables fast and dense single-molecule localization with high accuracy
Single-molecule localization microscopy (SMLM) has had remarkable success in imaging cellular structures with nanometer resolution, but standard analysis algorithms necessitate the activation of only single isolated emitters which limits imaging speed and labeling density. Here, we overcome this maj...
Autores principales: | Speiser, Artur, Müller, Lucas-Raphael, Hoess, Philipp, Matti, Ulf, Obara, Christopher J., Legant, Wesley R., Kreshuk, Anna, Macke, Jakob H., Ries, Jonas, Turaga, Srinivas C. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611669/ https://www.ncbi.nlm.nih.gov/pubmed/34480155 http://dx.doi.org/10.1038/s41592-021-01236-x |
Ejemplares similares
-
Maximum-likelihood model fitting for quantitative analysis of SMLM data
por: Wu, Yu-Le, et al.
Publicado: (2022) -
Optimal 3D single-molecule localization in real time using experimental point spread functions
por: Li, Yiming, et al.
Publicado: (2018) -
Global fitting for high-accuracy multi-channel single-molecule localization
por: Li, Yiming, et al.
Publicado: (2022) -
MicroFPGA: An affordable FPGA platform for microscope control
por: Deschamps, Joran, et al.
Publicado: (2023) -
Optimizing imaging speed and excitation intensity for single molecule localization microscopy
por: Diekmann, Robin, et al.
Publicado: (2020)