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    • Thin wrapper around Microsoft FHIR Converter to allow for a standalone FHIR server that provides data conversion operations.
      C#
      MIT License
      1000Updated Jan 16, 2025Jan 16, 2025
    • Scala
      MIT License
      2891Updated Jan 16, 2025Jan 16, 2025
    • Sparsely Annotated Region and Organ Segmentation (SAROS) - A large, heterogeneous, and sparsely annotated segmentation dataset on CT imaging data
      Python
      MIT License
      73601Updated Jan 16, 2025Jan 16, 2025
    • FHIR-PYrate is a package that provides a high-level API to query FHIR Servers for bundles of resources and return the structured information as pandas DataFrames. It can also be used to filter resources using RegEx and SpaCy and download DICOM studies and series.
      Python
      MIT License
      1158114Updated Jan 16, 2025Jan 16, 2025
    • dcm4che based DICOM de-identification lib
      Scala
      3200Updated Jan 16, 2025Jan 16, 2025
    • With the DeidentiFHIR-Pipeline, you can transfer FHIR based data from one source (e.g. a FHIR server) to a target (e.g. a FHIR server) and pseudonymize the data in between. Pseudonymization is based on the DeidentiFHIR library.
      Java
      MIT License
      0110Updated Jan 14, 2025Jan 14, 2025
    • DOME

      Public
      Python
      MIT License
      0001Updated Jan 13, 2025Jan 13, 2025
    • DICOM-RST

      Public
      DICOMweb-compatible gateway server with DIMSE and S3 implementations
      Rust
      MIT License
      219132Updated Dec 20, 2024Dec 20, 2024
    • TypeScript
      MIT License
      01001Updated Oct 24, 2024Oct 24, 2024
    • BOA is a segmentation tool of CT scans by the SHIP-AI group (https://ship-ai.ikim.nrw/). Combining the TotalSegmentator and the Body Composition Analysis, this tool is capable of analyzing medical images and identifying the different structures within the human body, including bones, muscles, organs, and blood vessels.
      Python
      Apache License 2.0
      72632Updated Oct 4, 2024Oct 4, 2024
    • SALT

      Public
      Softmax for Arbitrary Label Trees (SALT) is a framework for training segmentation networks using conditional probabilities to model hierarchical relationships in the data.
      Python
      MIT License
      67711Updated Oct 4, 2024Oct 4, 2024
    • A library that implements websocket functionality in Scala 2
      Scala
      0001Updated Mar 28, 2024Mar 28, 2024
    • Python
      MIT License
      0423Updated Mar 13, 2024Mar 13, 2024
    • Python
      MIT License
      0105Updated Oct 25, 2023Oct 25, 2023
    • Scala
      MIT License
      0302Updated Jul 25, 2023Jul 25, 2023