Super‐Resolution Near‐Infrared Fluorescence Microscopy of Single‐Walled Carbon Nanotubes Using Deep Learning

Abstract

Single‐Walled Carbon Nanotubes In article number http://doi.wiley.com/10.1002/adpr.202200244, Gili Bisker and co‐workers develop a fast, parameter‐free, computational method for enhancing the spatial resolution of near‐infrared fluorescence images of single‐walled carbon nanotubes (SWCNTs), utilizing the advantages of deep learning and convolutional neural networks. The approach is demonstrated for a wide range of imaging conditions, including real‐time videos, without compromising the temporal resolution.