7T MRI-Synthesized Iron and Myelin Histology by Deep Learning
Motivation: Advanced MRI techniques aim to evaluate the existence of iron and myelin but still face limitations, particularly in white matter regions. Histological staining remains the gold standard due to its precision in assessing myelin and iron levels. Goal(s): To synthesize histological images of iron and myelin staining from MRI. Approach: Use deep learning to create histology-like staining images from multi-contrast MRI. Results: Deep learning successfully generated high-resolution iron and myelin staining images. Impact: Our research shows that deep learning can synthesize myelin and iron stainings from multi-contrast MRI. This technique enhances understanding of brain development, function, and diseases, promising advances in medical imaging and histology.
Authors
- Günther Grabner (ORCID: https://orcid.org/0000-0001-8330-8446)
- Wolfgang Bogner (ORCID: https://orcid.org/0000-0002-0130-3463)
- Simon Hametner (ORCID: https://orcid.org/0000-0002-5160-5208)
- Beata Bachrátá (ORCID: https://orcid.org/0000-0002-3352-8966)
- Romana Höftberger (ORCID: https://orcid.org/0000-0002-5769-1100)
- Sutatip Pittayapong
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/10.58530/2025/1201
- Primary Topic
- Digital Imaging for Blood Diseases
- Type
- article
- Field-Weighted Citation Impact
- 0.00