| license: gpl-3.0 | |
| # Pre-trained Deep Learning Segmentation Models for ACE Pipeline | |
| ## AI-based Cartography of Ensembles (ACE) Pipeline Highlights | |
| - Cutting-edge vision transformer and CNN-based deep learning architectures trained on large LSFM datasets to map brain-wide local/laminar neuronal activity. | |
| - Optimized cluster-wise statistical analysis with a threshold-free enhancement approach to chart subpopulation-specific effects at the laminar and local levels, without restricting the analysis to atlas-defined regions. | |
| - Modules for providing deep learning model uncertainty estimates and fine-tuning. | |
| - Interface with [MIRACL](https://miracl.readthedocs.io/en/latest/index.html) registration. | |
| - Ability to map the connectivity between clusters of activations. | |
| 📖 **Read the full article here:** [LINK](https://www.nature.com/articles/s41592-024-02583-1) | |
| 🔗 **MIRACL Software:** [LINK](https://miracl.readthedocs.io/en/latest/index.html) | |
| 🔗 **ACE Installation Page:** [LINK](https://miracl.readthedocs.io/en/latest/tutorials/workflows/ace_flow/ace_flow.html) | |