When less is more: optimising fluorescence microscopy with Micro𝕊plit

Researchers at Human Technopole have developed a novel machine learning-based method that transforms composite fluorescence microscopy images with overlapping signals into separate images revealing individual cellular structures. The tool is published in Nature Methods, with experimental models and training data openly available on GitHub. The post When less is more: optimising fluorescence microscopy with Micro𝕊plit appeared first on Human Technopole .