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bioRxiv · 10.1101/2024.06.03.597232

Piximi - An Images to Discovery web tool for bioimages and beyond

Moser, L. M.·Gogoberidze, N.·Papaleo, A.·Lucas, A.·Dao, D.·Friedrich, C. A.·Paavolainen, L.·Molnar, C.·Stirling, D. R.·Hung, J.·Wang, R.·Tromans-Coia, C.·Li, B.·Evans, E. L.·Eliceiri, K. W.·Horvath, P.·Carpenter, A. E.·Cimini, B. A.
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Abstract

Deep learning has greatly accelerated research in biological image analysis yet it often requires programming skills and specialized tool installation. Here we present Piximi, a modern, no-programming image analysis tool leveraging deep learning. Implemented as a web application at Piximi.app, Piximi requires no installation and can be accessed by any modern web browser. Its client-only architecture preserves the security of researcher data by running all computation locally. Piximi offers four core modules: a deep learning classifier, an image annotator, measurement modules, and pre-trained deep learning segmentation modules. Piximi is interoperable with existing tools and workflows by supporting import and export of common data and model formats. The intuitive researcher interface and easy access to Piximi allows biological researchers to obtain insights into images within just a few minutes. Piximi aims to bring deep learning-powered image analysis to a broader community by eliminating barriers to entry.

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Moser, L. M., Gogoberidze, N., Papaleo, A., Lucas, A., Dao, D., Friedrich, C. A., Paavolainen, L., Molnar, C., Stirling, D. R., Hung, J., Wang, R., Tromans-Coia, C., Li, B., Evans, E. L., Eliceiri, K. W., Horvath, P., Carpenter, A. E., Cimini, B. A.. 2024-06-04. Piximi - An Images to Discovery web tool for bioimages and beyond. https://doi.org/10.1101/2024.06.03.597232

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