Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Towards Interoperable ECGs: Converting Proprietary XML to DICOM.

Lennart Graf1, Maximilian Oremek2,3, Ruwen Sadocco4

  • 1Dpt. of Medical Informatics, University Medical Center Göttingen, Germany.

Studies in Health Technology and Informatics
|May 17, 2025
PubMed
Summary

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Persisting Intensive Care Unit (ICU) Monitoring Data in HDF5.

Studies in health technology and informatics·2026
Same author

Meet NUM-ENRICH: A Collaborative National Effort to Extend and Harmonize Research Infrastructures Within the German Network University Medicine.

Studies in health technology and informatics·2026
Same author

Make Open Source Compliant: Validation in Non-Interventional Clinical Studies.

Studies in health technology and informatics·2026
Same author

The Somnolink-Hub: A Central Infrastructure That Unites Sleep Data at Point of Care.

Studies in health technology and informatics·2026
Same author

Participatory Technology Assessment in AI Development for Sleep Medicine.

Studies in health technology and informatics·2026
Same author

Utilizing Routine Care Data of Rare Diseases: Challenges, Chances and Call for Collaboration.

Studies in health technology and informatics·2026
Same journal

A GenAI Pipeline for Violinist Kinematic Data Management.

Studies in health technology and informatics·2026
Same journal

AMAL-For-Qatar: A Comprehensive AI Ecosystem for Fetal Ultrasound Analysis - Project Overview and Achievements.

Studies in health technology and informatics·2026
Same journal

Longitudinal Treatment-Aware Multimodal AI for Dermatology: A Scoping Review.

Studies in health technology and informatics·2026
Same journal

Predicting Postpartum Depression Using Imbalance-Aware Machine Learning.

Studies in health technology and informatics·2026
Same journal

Validation of Deep-Learning Models for Autosegmentation of Brain Metastases.

Studies in health technology and informatics·2026
Same journal

Delay-Dependent Gating in Modular RNNs.

Studies in health technology and informatics·2026
See all related articles
This summary is machine-generated.

This study developed an open-source converter to transform proprietary Electrocardiogram (ECG) data into the DICOM standard, improving cardiovascular data interoperability. The tool ensures standardized data representation for better disease detection and research.

Area of Science:

  • Cardiology
  • Medical Informatics
  • Health Data Standards

Background:

  • Electrocardiograms (ECGs) are crucial for diagnosing cardiovascular diseases.
  • Limited interoperability of ECG data hinders healthcare data exchange.
  • The ACRIBiS project aims to create a FAIR ECG data infrastructure in Germany.

Purpose of the Study:

  • To present an open-source converter for transforming proprietary ECG XML files into the DICOM format.
  • To ensure standardized data representation for ECGs.
  • To enhance the interoperability of cardiovascular data.

Main Methods:

  • Developed a general-purpose converter for ECG data.
  • Processed ECG raw data, metadata, and waveform annotations.
  • Utilized value codes from medical terminologies like SCP-ECG.
Keywords:
DICOMData standardsECGElectrocardiogramInteroperability

Related Experiment Videos

  • Evaluated the converter on 36,933 clinical ECGs from GE Healthcare Muse®.

    • Main Results:

    • The converter demonstrated high performance in transforming ECG data.
    • The output data complied with Digital Imaging and Communications in Medicine (DICOM) standards.
    • Successfully processed metadata and annotations alongside raw ECG data.

    Conclusions:

    • The developed converter effectively addresses ECG data interoperability challenges.
    • The tool facilitates standardized ECG data representation, crucial for research and clinical practice.
    • Future work includes expanding vendor compatibility and workflow integration.