Transforming a clinical study database into a structured database adapted to artificial intelligence applications
Clinical trial imaging databases are not adapted for AI model development. A curation process of MRI databases was developed for machine learning applications. We share the open-source tools and methodology developed in this study.
Authors
- I. Thomassin Naggara
- Nicolas Perrot (ORCID: https://orcid.org/0000-0002-2395-2333)
- Carole Lazarus (ORCID: https://orcid.org/0000-0003-2329-9423)
- Patrice Taourel (ORCID: https://orcid.org/0000-0001-6465-1919)
- Florence Cloppet (ORCID: https://orcid.org/0000-0002-4807-299X)
- Camille Kurtz (ORCID: https://orcid.org/0000-0001-9254-7537)
- Thibault Sauron
- Ingrid Millet
- Édouard Poncelet
- EURAD Study Group
- Marc Bazot
- Caroline Malhaire
- Aurelie Jalaguier-Coudray
- Laure Fournier
- Valerie Juhan
- Corinne Balleyguier
- Emile Darai
Institutions
- Inserm (FR)
- Université de Montpellier (FR)
- Université Paris Cité (FR)
- Institut Gustave Roussy (FR)
- Sorbonne Université (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Hôpital Européen Georges-Pompidou (FR)
- Hôpital Européen (FR)
- Paris Cardiovascular Research Center (FR)
- Institut Paoli-Calmettes (FR)
- Centre Hospitalier de Valenciennes (FR)
- Hôpital de la Timone (FR)
- Philips (France) (FR)
- Hôpital Tenon (FR)
- Institut Curie (FR)
Publication Details
- Journal
- Insights into Imaging
- Published
- 2026-02-16
- DOI
- https://doi.org/10.1186/s13244-025-02087-2
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00