Towards Reproducible and Resource‐Efficient Perfusion Imaging Analysis for African Dementia Imaging Research
Using simulated (OSIPI-ASL) and real-world (PREVENT-AD) data, we aim to assess the feasibility of a resource-efficient image processing tool for reproducible ASL data analysis. Once implemented, we will share our approach for wider use in RCS to enable inclusive and reproducible imaging research.
Authors
- Kesavi Kanagasabai
- Cristián Montalba (ORCID: https://orcid.org/0000-0003-3370-0233)
- Abdalla Z. Mohamed (ORCID: https://orcid.org/0000-0003-4499-672X)
- Alfonso Fajardo
- Jasmine D. Cakmak (ORCID: https://orcid.org/0000-0002-5197-234X)
- Confidence Raymond (ORCID: https://orcid.org/0000-0003-3927-9697)
- Olusola Aremu (ORCID: https://orcid.org/0009-0004-9882-379X)
- Channelle Tham
- Ethan C Draper
- Charity Umoren
- Cynthia Isabel Smith
- Nsiah Donkor Anita
- Philip Nkwam
- Oluwateniola Akinwale
- Kelvin Murithi
- Issac Tigbee
- Udunna Anazodo
- Harrison Aduluwa
Institutions
- New York University Abu Dhabi (AE)
- Western University (CA)
- Lagos State University (NG)
- Montreal Neurological Institute and Hospital (CA)
- Johns Hopkins University (US)
- Radboud University Nijmegen (NL)
- Pontificia Universidad Católica de Chile (CL)
- University of Lagos (NG)
- Aga Khan University Nairobi (KE)
- National Nurses Association of Kenya (KE)
- Artificial Intelligence in Medicine (Canada) (CA)
- McGill University (CA)
- University for Development Studies (GH)
Publication Details
- Journal
- Alzheimer s & Dementia
- Published
- 2025-12-01
- DOI
- https://doi.org/10.1002/alz70856_104135
- Primary Topic
- Advanced MRI Techniques and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00