llnl/LEAP
comprehensive library of 3D transmission Computed Tomography (CT) algorithms with Python and C++ APIs, a PyQt GUI, and fully integrated with PyTorch
LEAP implements high-accuracy forward and back projectors via CUDA kernels optimized for multi-GPU and multi-core CPU execution, with PyTorch bindings enabling fully differentiable CT operations for end-to-end learning. The library includes physics-based correction algorithms (scatter, beam hardening, dual-energy decomposition) through integration with XrayPhysics, and demonstrates superior reconstruction quality—achieving 1.7× higher SNR than comparable packages like ASTRA on standard benchmarks.
220 stars. No commits in the last 6 months.
Stars
220
Forks
28
Language
Cuda
License
MIT
Category
Last pushed
Sep 26, 2025
Commits (30d)
0
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