Evaluation of two AI techniques for the detection of new T2/FLAIR lesions in the follow-up of multiple sclerosis patients
Both AI software have been found to enhance NL detection in MS patients, outperforming standard methods. These tools offer crucial advantages for accurate disease monitoring.
Authors
- François Cotton (ORCID: https://orcid.org/0000-0003-0046-2478)
- Jasmina Boban (ORCID: https://orcid.org/0000-0001-9701-5484)
- Verónica Muñoz-Ramírez (ORCID: https://orcid.org/0000-0002-0975-7064)
- Marie Blanchère
- Christian Federau (ORCID: https://orcid.org/0000-0002-3803-6602)
- Myriam Edjlali (ORCID: https://orcid.org/0000-0002-4239-0831)
- Milica Mastilović (ORCID: https://orcid.org/0009-0005-7771-6167)
- Olivier Heinzlef (ORCID: https://orcid.org/0000-0002-4634-8542)
Institutions
- Université Claude Bernard Lyon 1 (FR)
- Centre National de la Recherche Scientifique (FR)
- Inserm (FR)
- University of Novi Sad (RS)
- University of Zurich (CH)
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Université Paris-Saclay (FR)
- Kyoto Prefectural University of Medicine (JP)
- Institut d'Imagerie Biomédicale (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Oncology Institute of Vojvodina (RS)
- Centre Hospitalier Intercommunal de Poissy (FR)
- Hôpital Lyon Sud (FR)
- CEA Paris-Saclay (FR)
- Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé (FR)
- Phylonix (United States) (US)
Publication Details
- Journal
- Frontiers in Neurology
- Published
- 2025-10-08
- DOI
- https://doi.org/10.3389/fneur.2025.1678073
- Citations
- 1
- Primary Topic
- Multiple Sclerosis Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.47
Funders
- Agence Nationale de la Recherche