SABER⚔️ — Segment Anything Based Electron Tomography Recognition

Welcome to the documentation for SABER, a robust, open-source platform for autonomous segmentation of organelles in cryo-electron tomography (cryo-ET) and electron microscopy (EM) datasets.

SABER leverages state-of-the-art foundational models to enable:

• Zero-shot segmentation of EM/cryo-ET data
• Interactive annotation with a user-friendly GUI
• Expert-driven classifier training for improved accuracy
• 3D organelle reconstruction from tomographic data

🚀 What Can You Do With SABER?

• Pre-process and curate your microscopy data for segmentation
• Train custom classifiers using your own expert annotations
• Run inference for both 2D and 3D segmentation tasks
• Visualize and refine results interactively

💡 Why SABER?

SABER is designed for researchers who want to:

• Accelerate organelle segmentation in large EM/cryo-ET datasets
• Combine the power of foundational models with expert curation
• Seamlessly move from raw data to publication-ready segmentations in both 2D and 3D.

📚 Tutorials

SABER can be used both from the command line (CLI) and as a Python library (API). Choose the workflow that fits your needs. Follow the quick start guide to learn the core commands to develop segmentations.

🖥️ CLI Tutorials

Use SABER from the command line for quick, scriptable workflows:

• Pre-processing Your Data: Prepare your EM/cryo-ET datasets for segmentation and annotation. Use the interactive GUI to annotate segmentations and
• Training a Classifier: With the annotations, train a domain expert classifier.
• Inference in 2D & 3D: Apply your trained models to generate high-quality segmentations in both 2D and 3D.
• Refine Membranes: Clean up organelle and membrane segmentations using GPU-optimized morphological filtering.

🐍 API Tutorials

Integrate SABER into your own Python scripts and notebooks:

• API Overview: Comprehensive introduction to the SABER Python API
• 2D Quickstart: Learn how to segment 2D micrographs programmatically
• 2D Workflow Tutorial: Complete 2D pipeline with preprocessing, training, and inference
• 3D Quickstart: Learn how to segment 3D tomograms programmatically
• 3D Workflow Tutorial: Complete 3D pipeline with video propagation and advanced features

🙋‍♂️ Getting Help

Visit our GitHub repository for source code and issues.

Ready to get started? Check out the Quick Start or the API Overview!