Deep learning-powered denoising technique for high-speed dynamic fluorescence imaging
A new deep learning-based approach has been developed to overcome one of the critical limitations in fluorescence microscopy: severe image degradation caused by noise in dynamic in vivo imaging environments. The technique, recently published in PhotoniX (May 23, 2025), introduces a self-supervised denoising network—TeD (Temporal-gradient empowered Denoising)—that improves image quality without requiring clean reference images, representing a breakthrough for applications involving rapid biological ...