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DICOMautomaton

imported

software/dicomautomaton

A multipurpose tool for medical physics.

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

DICOMautomaton project image
GitHub preview card for hdclark/DICOMautomaton. Served by its origin, not stored here, and not covered by this registry’s licence.
record
Category
Software & Systems
Subcategory
unknown
License
GPL-3.0(osi)
Status
active
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
halclark.ca
Documentation
unknown
Tags
contours · dicom · dose · image-analysis · image-processing · medical-physics · perfusion · point-clouds
Regulatory
unknown
built by · 6

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.

  • RespiRatecontours · medical-physics

    Software-defined approach to measuring mice respiratory rates

  • osipyimage-processing · perfusion

    Python package for perfusion MRI analysis

  • CARPIdicom · perfusion

    The Cancer Radiomic and Perfusion Imaging (CARPI) automated framework is a Python-based software for radiomic and perfusion feature extraction developed by the ABASTI laboratory at MD Anderson…

  • OpenXRayMCdicom · dose

    Monte Carlo radiation dose scoring application for diagnostic x-ray imaging

  • STARdicom · dose

    Statistical Toolkit for Analysis of Radiotherapy DICOM Data

  • aidsorbpoint-clouds

    Python package for deep learning on porous materials and beyond.

sources
  1. api.github.com/repos/hdclark/DICOMautomaton
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2026-07-08, 89 stars, license reported as GPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.

Not yet verified by a human. Correct this record →

machine-readable

/v1/entries/31.json→ .entries["dicomautomaton"]

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