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YeaZ is an innovative open-source software tool designed specifically for the scientific community to automate the segmentation and tracking of yeast cells in microscopy images. Developed by researchers at the Laboratory of Physics of Biological Systems (LPBS) at EPFL in Switzerland, the tool leverages advanced convolutional neural networks to provide high-accuracy data for biological research. The project was born out of a need for more efficient and precise imaging processing in microbiology.
As an academic and open-source project, YeaZ is primarily maintained by the Rahi Lab at EPFL. It represents a collaborative effort in the fields of quantitative systems biology and deep learning, being distributed under the MIT license. This allows researchers worldwide to contribute to its development and use it freely for non-commercial and commercial scientific purposes alike, ensuring the software remains at the cutting edge of biotechnological research tools.
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