151 citations · 488 across the 19 of their papers we have counts for
23 papers
Live-cell imaging powered by computation
Hari Shroff, Ilaria Testa, Florian Jug +1
The proliferation of microscopy methods for live-cell imaging offers many new possibilities for users but can also be challenging to navigate. We focus here on computational method…
DeepContrast: Deep Tissue Contrast Enhancement using Synthetic Data Degradations and OOD Model Predictions
Nuno Pimpão Martins, Yannis Kalaidzidis, Marino Zerial +1
Microscopy images are crucial for life science research, allowing detailed inspection and characterization of cellular and tissue-level structures and functions. However, microscop…
Better Research Software Tools to Elevate the Rate of Scientific Discovery -- or why we need to invest in research software engineering
Joran Deschamps, Damian Dalle Nogare, Florian Jug
In the past decade, enormous progress has been made in advancing the state-of-the-art in bioimage analysis - a young computational field that works in close collaboration with the…
bAIoimage analysis: elevating the rate of scientific discovery -- as a community
Damian Edward Dalle Nogare, Matthew Hartley, Joran Deschamps +2
The future of bioimage analysis is increasingly defined by the development and use of tools that rely on deep learning and artificial intelligence (AI). For this trend to continue…
Community-developed checklists for publishing images and image analysis
Christopher Schmied, Michael Nelson, Sergiy Avilov +51
Images document scientific discoveries and are prevalent in modern biomedical research. Microscopy imaging in particular is currently undergoing rapid technological advancements. H…
N2V2 -- Fixing Noise2Void Checkerboard Artifacts with Modified Sampling Strategies and a Tweaked Network Architecture
Eva Höck, Tim-Oliver Buchholz, Anselm Brachmann +2
In recent years, neural network based image denoising approaches have revolutionized the analysis of biomedical microscopy data. Self-supervised methods, such as Noise2Void (N2V),…