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...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-58274-8 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Be the first to leave a comment!