Bioimaging has made tremendous advances in this century. Innovations in high-and super-
resolution microscopy are well established, and live-cell imaging is extensively used to gain …

Advances in imaging, segmentation and tracking have led to the routine generation of large
and complex microscopy datasets. New tools are required to process this 'phenomics' type …

Eukaryotic genomes are highly compacted within the nucleus and organized into complex
3D structures across various genomic and physical scales. Organization within the nucleus …

Optical microscopy is an indispensable tool in life sciences research, but conventional
techniques require compromises between imaging parameters like speed, resolution, field …

Correlative light and volume electron microscopy (vCLEM) is a powerful imaging technique
that enables the visualisation of fluorescently labelled proteins within their ultrastructural …

U-Net is a convolutional neural network model developed in 2015 and has proven to be one
of the most inspiring deep-learning models for image segmentation. Numerous U-Net-based …

Intravital microscopy (IVM) enables live imaging of animals at single-cell level, offering
essential insights into cancer progression. This technique allows for the observation of …

Phototoxicity in live-cell fluorescence microscopy can compromise experimental outcomes,
yet quantitative methods to assess its impact remain limited. Here we present PhotoFiTT …

BiaPy is an open-source library and application that streamlines the use of common deep
learning approaches for bioimage analysis. Designed to simplify technical complexities, it …

Phototoxicity in live-cell fluorescence microscopy can compromise experimental outcomes,
yet quantitative methods to assess its impact remain limited. Here we present PhotoFiTT …