Improved Dementia Prediction in Cerebral Small Vessel Disease Using Deep Learning–Derived Diffusion Scalar Maps From T1
We have developed a fast and generalizable method to synthesize FA/MD maps from T1 to improve the prediction accuracy of dementia in small vessel disease when diffusion tensor imaging data have not been acquired.
Authors
- Rui Li (ORCID: https://orcid.org/0000-0003-0555-3176)
- Anil M. Tuladhar (ORCID: https://orcid.org/0000-0002-4815-2834)
- Hugh S. Markus (ORCID: https://orcid.org/0000-0002-9794-5996)
- Yutong Chen (ORCID: https://orcid.org/0000-0001-8024-8775)
- Daniel J. Tozer (ORCID: https://orcid.org/0000-0002-0404-3214)
- Frank‐Erik de Leeuw (ORCID: https://orcid.org/0000-0003-2221-3026)
- Hao Li (ORCID: https://orcid.org/0000-0002-2125-9092)
Institutions
- Radboud University Nijmegen (NL)
- University of Cambridge (GB)
- Radboud University Medical Center (NL)
Publication Details
- Journal
- Stroke
- Published
- 2024-08-15
- DOI
- https://doi.org/10.1161/strokeaha.124.047449
- Citations
- 8
- Primary Topic
- Acute Ischemic Stroke Management
- Type
- article
- Field-Weighted Citation Impact
- 3.09
Funders
- National Institute for Health and Care Research
- British Heart Foundation
- Department of Health and Social Care
- University of Cambridge
- Radboud Universiteit
- Cambridge University Hospitals