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<p>This paper describes PARADIM, a digital infrastructure designed to support research at the interface of data science and medical imaging, with a focus on Research Data Management best practices. The platform is built from open-source components and rooted in the FAIR principles through strict compliance with the DICOM standard. It addresses key needs in data curation, governance, privacy, and scalable resource management. Supporting every stage of the data science discovery cycle, the platform offers robust functionalities for user identity and access management, data de-identification, storage, annotation, as well as model training and evaluation. Rich metadata are generated all along the research lifecycle to ensure the traceability and reproducibility of results. PARADIM hosts several medical image collections and allows the automation of large-scale, computationally intensive pipelines (e.g., automatic segmentation, dose calculations, AI model evaluation). The platform fills a gap at the interface of data science and medical imaging, where digital infrastructures are key in the development, evaluation, and deployment of innovative solutions in the real world.</p>

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PARADIM: A Platform to Support Research at the Interface of Data Science and Medical Imaging

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年6月3日

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  • Yannick Lemaréchal,
  • Gabriel Couture,
  • François Pelletier,
  • Ronan Lefol,
  • Pierre-Luc Asselin,
  • Samuel Ouellet,
  • Jérémie Bernard,
  • Leyla Ebrahimpour,
  • Venkata S. K. Manem,
  • Johanna Topalis,
  • Balthasar Schachtner,
  • Sébastien Jodogne,
  • Philippe Joubert,
  • Katharina Jeblick,
  • Michael Ingrisch,
  • Philippe Després

摘要

This paper describes PARADIM, a digital infrastructure designed to support research at the interface of data science and medical imaging, with a focus on Research Data Management best practices. The platform is built from open-source components and rooted in the FAIR principles through strict compliance with the DICOM standard. It addresses key needs in data curation, governance, privacy, and scalable resource management. Supporting every stage of the data science discovery cycle, the platform offers robust functionalities for user identity and access management, data de-identification, storage, annotation, as well as model training and evaluation. Rich metadata are generated all along the research lifecycle to ensure the traceability and reproducibility of results. PARADIM hosts several medical image collections and allows the automation of large-scale, computationally intensive pipelines (e.g., automatic segmentation, dose calculations, AI model evaluation). The platform fills a gap at the interface of data science and medical imaging, where digital infrastructures are key in the development, evaluation, and deployment of innovative solutions in the real world.