Brain tumor enhancement prediction from pre-contrast conventional weighted images using synthetic multiparametric mapping and generative artificial intelligence
Our results suggest the feasibility to predict T1-weighted-enhanced tissues from pre-contrast conventional weighted images using deep learning for the synthesis of parametric maps.
Authors
- Laura Nuñez-Gonzalez
- Carlos Alberola‐López (ORCID: https://orcid.org/0000-0003-3684-0055)
- Juan A. Hernández‐Tamames
- Rodrigo de Luis‐García (ORCID: https://orcid.org/0000-0001-5023-6490)
- Elisa Moya‐Sáez (ORCID: https://orcid.org/0000-0003-4945-3193)
Institutions
- Universidad de Valladolid (ES)
- Erasmus MC (NL)
- Erasmus University Rotterdam (NL)
- Delft University of Technology (NL)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2024-12-31
- DOI
- https://doi.org/10.21037/qims-24-721
- Citations
- 3
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.35
Funders
- Fundación Científica Asociación Española Contra el Cáncer
- Ministerio de Ciencia e Innovación
- Fundación Bancaria Caixa d'Estalvis i Pensions de Barcelona
- Fundação para a Ciência e a Tecnologia