TY - BOOK AU - Birk, Udo T1 - Deep Learning in Microscopy T2 - Imaging ONEWORLD series CY - Online, 19. Juli A2 - Royal Microscopial Society Y2 - 2021 AB - Recent advancements in microscopic image analysis have made use of the tremendous progress that artificial intelligence has seen in the evaluation of digital images. The application of deep learning techniques to microscopic image analysis ranges from image restoration and denoising to automated cellular and subcellular profiling to generation of augmented reconstructed image data, encompassing e.g. super-resolution images from single molecule localization microscopy data, virtual refocussing, content aware neuronal reconstructions and many more. However, deep learning methods are generally based on the availability of large amounts of reliable ground truth data. In the talk I will highlight some of the recent advances in deep learning applied to microscopic data with a focus on applications for super-resolution microscopy. M4 - Citavi ER -