openmedical/registry
← registry

LEAP

imported

software/leap

comprehensive library of 3D transmission Computed Tomography (CT) algorithms with Python and C++ APIs, a PyQt GUI, and fully integrated with PyTorch

Machine-generated from the listed sources and not yet reviewed by a human.

LEAP project image
GitHub preview card for llnl/LEAP. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
MIT(osi)
Status
active
Maturity
deployed
Organization
llnl
Country
unknown
Documentation
unknown
Tags
abel-transform · artificial-intelligence · beamhardening · bhc · computed-tomography · cone-beam · ct · helical-reconstruction
Regulatory
unknown
built by · 3

Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.

similar by tags

Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.

  • 3DCuratorcomputed-tomography · ct

    A 3D Viewer for CTs of Polychromed Wood Sculptures

  • COVID19-intensity-labelingcomputed-tomography · ct

    Code for COVID19 CT labeling. Submillimetric CT dataset provided as well.

  • CT-preprocesscomputed-tomography

    Preprocess head CT scans using python!

  • DenoMambacomputed-tomography

    Official implementation of DenoMamba: A fused state-space model for low-dose CT denoising

  • ldct-benchmarkcomputed-tomography

    A benchmark for deep learning-based low dose CT image denoising

  • LuVoXcomputed-tomography

    Workflow-centred open-source fully automated lung volumetry in chest CT.

sources
  1. api.github.com/repos/llnl/LEAP
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-07-25, 244 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/51.json→ .entries["leap"]

Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.