WebOct 9, 2024 · Based on deep learning networks, we develop a single-frame super-resolution microscopy (SFSRM) approach that reconstructs a super-resolution image from a single … WebSpeiser, A., Turaga, S. C. & Macke, J. H. Teaching deep neural networks to localize sources in super-resolution microscopy by combining simulation-based learning and unsupervised learning. Preprint at (2024) ... Liu, T. et al. Deep learning-based super-resolution in coherent imaging systems. Sci. Rep. 9, 3926 (2024).
Rationalized deep learning super-resolution microscopy …
WebApr 20, 2024 · We show that deep learning attains super-resolution with challenging contrast-agent densities, both in-silico as well as in-vivo. Deep-ULM is suitable for real-time applications, resolving about 70 high-resolution patches (128x128 pixels) per second on a standard PC. Exploiting GPU computation, this number increases to 1250 patches per … WebSep 10, 2024 · Harnessing deep learning Single-molecule localization microscopy (SMLM) is now an invaluable super-resolution microscopy to image cellular structures with … mykchartchart sign-in
Deep learning-based super-resolution fluorescence microscopy on …
WebBiological super-resolution microscopy is a new generation of imaging techniques that overcome the ~200 nm diffraction limit of conventional light microscopy in spatial resolution. ... Yang Tianjie, Luo Yaoru, Ji Wei, Yang Ge. Advancing biological super-resolution microscopy through deep learning: a brief review[J]. Biophysics Reports, 2024, … Weband transformative role in the development of super-resolution microscopy. We conclude with an outlook on how deep learning could shape the future of this new generation of light microscopy technology. Keywords: super-resolution microscopy, image super-resolution, fluorescence microscopy, deep learning, image reconstruction mykchart richland wa log in