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The facility provides access to proprietary analysis software, open source software and tools developed in house. We also provide access to deep-learning solutions including the training on your own data on our machines.
Designed to analyze multi-color data simply, efficiently and quickly. Four simple control panels provide access to all aspects of your data.
2D image analysis software. Allows to work with image in the LEICA format. Possibility to analyse FRAP experiments.
Programming language for numerical calculation with a focus on data analysis, algorithm development and the creation of mathematical models.
Image processing and analysis software.
Software that does 3D volume and surface rendering and allows to position, measure, annotate and modify 3D objects.
A novel concept of a web-based morphodynamic browser to visualise and interact with complex datasets, with applications in research and teaching.
Noise2Void is a deep-learning method that can be used to denoise microscopy images. No specific training datasets are required, only your noisy images. One noisy image is sufficient to train a network. Use dl4mic to train and apply the Noise2Void.
Enables researchers of all levels of flow cytometry experience to perform efficient sample acquisition and analysis. The software automates multiple fluidic functions, eliminating cumbersome and time consuming procedures
From the microscope to publication, OMERO handles all your images in a secure central repository. You can view, organize, analyze and share your data from anywhere you have internet access.
A number of image processing and analysis software packages are available on our analysis computers. Please contact us if you need help with on of the software packages.
A number of open source image analysis software packages are available on our computers. Other open source packages can be installed on demand. Most of our computers are equipped for 3D/4D processing and also for training and applying deep learning solutions. If you need help with a open source image analysis software please contact us.
Analysis tools and extensions developed at MRI. You can find the complete list of publicly available tools we developed in our github. Please contact us if you have an unsolved image analysis problem. We can either point you to already existing solutions of develop a custom tool for you.
We developed a tool dl4mic, that allows are users to train and run deep learning solutions from a graphical user interface integrated into FIJI/ImageJ. Currently 4 network-models are available within the tool: UNet, Dense-UNet, Noise2Void and Stardist. The tool allows to quickly integrate further models. For cell-segmentation we propose Cellpose. Cellpose is already trained with a large number of cell images and can often be used without further training. Our version of cellpose allows to run batch processing from within the graphical user interface.