Enabling new insights from old scans by repurposing clinical MRI archives for multiple sclerosis research
Abstract Magnetic resonance imaging (MRI) biomarkers are vital for multiple sclerosis (MS) clinical research and trials but quantifying them requires multi-contrast protocols and limits the use of abundant single-contrast hospital archives. We developed MindGlide, a deep learning model to extract br...
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| Main Authors: | Philipp Goebl, Jed Wingrove, Omar Abdelmannan, Barbara Brito Vega, Jonathan Stutters, Silvia Da Graca Ramos, Owain Kenway, Thomas Rossor, Evangeline Wassmer, Douglas L. Arnold, D. Louis Collins, Cheryl Hemingway, Sridar Narayanan, Jeremy Chataway, Declan Chard, Juan Eugenio Iglesias, Frederik Barkhof, Geoff J. M. Parker, Neil P. Oxtoby, Yael Hacohen, Alan Thompson, Daniel C. Alexander, Olga Ciccarelli, Arman Eshaghi |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-58274-8 |
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