llnl/LEAP
comprehensive library of 3D transmission Computed Tomography (CT) algorithms with Python and C++ APIs, a PyQt GUI, and fully integrated with PyTorch
This project helps scientists and engineers accurately reconstruct 3D images from X-ray computed tomography (CT) scans. You input raw CT projection data, and it outputs a high-quality 3D reconstructed image of the object. It's designed for researchers and practitioners working with CT imaging in fields like materials science, industrial inspection, or medical imaging.
220 stars. No commits in the last 6 months.
Use this if you need precise 3D reconstructions from CT data, especially when working with AI/ML models for advanced analysis or requiring physics-based corrections like scatter and beam hardening.
Not ideal if you need GPU support on a Mac, as some features and GPU capabilities are currently unavailable for that platform.
Stars
220
Forks
28
Language
Cuda
License
MIT
Category
Last pushed
Sep 26, 2025
Commits (30d)
0
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