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CTLabeling

imported

software/ctlabeling

A simple privacy-focused web panel in flask for labeling CT Scan's slices

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

record
Category
Software & Systems
Subcategory
unknown
License
GPL-3.0(osi)
Status
dormant
Maturity
deployed
Organization
unknown
Country
unknown
Homepage
unknown
Repository
github.com/IAmS4n/CTLabeling
Documentation
unknown
Tags
covid19 · ct-scans · dicom · dicom-viewer · dicom-web-viewer · dicomweb · flask · labeling
Regulatory
unknown
built by · 2

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.

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    A Framework which could create proxy for ORTHANC (Legacy PACS DICOM) in local networks with self signed SSL Which would work flawless with multiple security features.

  • DicomSCPdicom · dicom-viewer · dicomweb

    中文开源社区高完成度的 DICOM / PACS 基础服务组件

  • DICOMweb-jsdicom · dicom-viewer · dicomweb

    DICOMweb JavaScript client with viewer demo for consuming DICOM Web Services - (QIDO-RS, WADO-RS, WADO-URI, STOW-RS) part 18

  • react-cornerstone-exampledicom · dicom-web-viewer

    example integrating react with cornerstone.js library for viewing DICOM medical images

  • ct-volume-preprocessingct-scans · dicom

    End-to-end Python CT volume preprocessing pipeline to convert raw DICOMs into clean 3D numpy arrays for ML. From paper Draelos et al. "Machine-Learning-Based Multiple Abnormality Prediction with…

sources
  1. api.github.com/repos/IAmS4n/CTLabeling
    retrieved 2026-08-05 · via github-api

    Machine-imported from GitHub search. Last push 2021-05-27, 29 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/32.json→ .entries["ctlabeling"]

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