Advanced microscopy enables us to acquire quantities of time-lapse images to visualize the
dynamic characteristics of tissues, cells or molecules. Microscopy images typically vary in …

Deep learning of artificial neural networks has become the de facto standard approach to
solving data analysis problems in virtually all fields of science and engineering. Also in …

Single-molecule localization microscopy (SMLM) has had remarkable success in imaging
cellular structures with nanometer resolution, but standard analysis algorithms require …

An outstanding challenge in single-molecule localization microscopy is the accurate and
precise localization of individual point emitters in three dimensions in densely labeled …

Video microscopy has a long history of providing insight and breakthroughs for a broad
range of disciplines, from physics to biology. Image analysis to extract quantitative …

Imaging of both the positions and orientations of single fluorophores, termed single-
molecule orientation-localization microscopy, is a powerful tool for the study of biochemical …

Deep learning-based data analysis methods have gained considerable attention in all fields
of science over the last decade. In recent years, this trend has reached the single-molecule …

Propelled by the striking advances in optical microscopy and deep learning (DL), the role of
imaging in lab-on-a-chip has dramatically been transformed from a silo inspection tool to a …

While critical to biological processes, molecular diffusion is difficult to quantify, and spatial
map** of local diffusivity is even more challenging. Here we report a machine-learning …

Deconvolution microscopy has been extensively used to improve the resolution of the wide-
field fluorescent microscopy, but the performance of classical approaches critically depends …