Classification of Parkinson’s disease by deep learning on midbrain MRI
Our data demonstrate excellent performance of a quantitative QSM-NMS marker and automated DL PD classification algorithms based on midbrain MRI, while suggesting potential further improvements. Clinical utility is supported but requires validation in earlier stage PD cohorts.
Authors
- Robert Chun Chen
- Ling Ling Chan (ORCID: https://orcid.org/0000-0001-7603-7334)
- Wenlu Hou (ORCID: https://orcid.org/0000-0001-8657-677X)
- Thomas Welton (ORCID: https://orcid.org/0000-0002-9503-2093)
- Weiling Lee (ORCID: https://orcid.org/0009-0003-4680-272X)
- Septian Hartono (ORCID: https://orcid.org/0000-0002-2411-442X)
- Ee Wei Lim (ORCID: https://orcid.org/0000-0002-9227-3748)
- Eng King Tan
- Celeste Chen
- Peik Yen Teh
- Louis Tan
- Kumar Manharlal Prakash (ORCID: https://orcid.org/0000-0002-4853-5026)
Institutions
- Singapore General Hospital (SG)
- Duke-NUS Medical School (SG)
- National Neuroscience Institute (SG)
Publication Details
- Journal
- Frontiers in Aging Neuroscience
- Published
- 2024-08-20
- DOI
- https://doi.org/10.3389/fnagi.2024.1425095
- Citations
- 18
- Primary Topic
- Parkinson's Disease Mechanisms and Treatments
- Type
- article
- Field-Weighted Citation Impact
- 6.64
Funders
- Medical Research Council
- National Medical Research Council