Convolutional neural network denoising in fluorescence lifetime imaging microscopy (FLIM)
Fluorescence lifetime imaging microscopy (FLIM) systems are limited by their slow
processing speed, low signal-to-noise ratio (SNR), and expensive and challenging …
processing speed, low signal-to-noise ratio (SNR), and expensive and challenging …
Deep learning-based super-resolution fluorescence microscopy on small datasets
Fluorescence microscopy has enabled a dramatic development in modern biology by
visualizing biological organ-isms with micrometer scale resolution. However, due to the …
visualizing biological organ-isms with micrometer scale resolution. However, due to the …
Overcoming the fundamental limitation of frequency-domain fluorescence lifetime imaging microscopy spatial resolution
We propose and demonstrate the first analytical model of the spatial resolution of frequency-
domain (FD) fluorescence lifetime imaging microscopy (FLIM) that explains how it is …
domain (FD) fluorescence lifetime imaging microscopy (FLIM) that explains how it is …
[图书][B] Overcoming fundamental limits of three-dimensional in vivo fluorescence imaging using machine learning
VV Mannam - 2022 - search.proquest.com
In vivo fluorescence imaging is a powerful tool for understanding and characterizing
biological systems. For example, with the help of in vivo fluorescence imaging, one can …
biological systems. For example, with the help of in vivo fluorescence imaging, one can …