Predicting Quantitative Myelin Images from Clinical Scans and DTI using Linear and Neural Network Models
Motivation: Quantitative myelin imaging methods are usually not included in clinical MRI scans for persons with multiple sclerosis. Goal(s): Predict macromolecular pool-size-ratio maps from standard clinical scans. Approach: Compare PSR map prediction results from linear model and neural network model. Results: Most of the relationship between clinical scans plus DTI and PSR maps is captured by a simple linear model and the more complex nonlinear model offers minimal improvements. Impact: Leveraging typical clinical scans to predict PSR maps using a simple linear model can improve diagnostic capabilities for multiple.
Authors
- Richard Dortch (ORCID: https://orcid.org/0000-0002-9978-2203)
- Ashley M. Stokes (ORCID: https://orcid.org/0000-0003-1137-5003)
- Francesca Bagnato (ORCID: https://orcid.org/0000-0001-9544-9019)
- Kayla Bohlke
Publication Details
- Journal
- Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
- Published
- 2025-09-16
- DOI
- https://doi.org/10.58530/2025/3402
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00