Generalizing microscope control in Python

Read the paper: Casas M. et al. 2021
We have developed an open-source platform for the control of light-microscopy setups, especially suitable for targeted-switching light microscopy. The software solution helps microscope builders, users, and developers, push forward their research by providing a robust and adaptable alternative for microscope alignment and control, image reconstruction and analysis using Napari image viewer, and microscope automation using scripting in Python, which we embedded in ImSwitch. ImSwitch successfully handles multicolor imaging in super-resolution microscopy, both in point-scanning and camera-based setups.

If you want to know more about ImSwitch visit our GitHub and readthedocs.

Resolution prediction in RESOLFT

Read the paper: Bodén et al. 2020
We developed a numerical simulation software to analyze the impact of reversibly switchable probes in RESOLFT imaging. The performance of fluorescence microscopy and nanoscopy is often discussed by the effective point spread function and the optical transfer function. However, due to the complexity of the fluorophore properties such as photobleaching or other forms of photoswitching, which introduce a variance in photon emission, it is not trivial to choose optimal imaging parameters and to predict the spatial resolution. In this tool, we implemented analytical theoretical framework for estimating the achievable resolution of a microscope depending on parameters such as photoswitching, labeling densities, exposure time and sampling.

Visit the GitHub page of the project.

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