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Fast and user-friendly segmentation of cryo-electron tomography data

annotate, train, and apply convolutional neural networks

Ais is a segmentation suite for cryo-electron tomography data that was designed to be fast, intuitive, and as easy to use as we could make it. Manually annotate a small section of your data, train a neural network in seconds, and apply it to segment entire datasets.

Watch the video introduction to Ais on YouTube.

Ais ecosystem

This repository comprises a standalone version of Ais. For the version integrated into the correlative microscopy data processing suite scNodes, see the scNodes repository. Trained models can be shared via the Ais model repository. Ais is also the foundation on which easymode - pretrained general networks for cellular cryoET - was built.

Need help?

Please post questions and bug reports on the Ais GitHub issues page.