Open Access Series of Imaging Studies (OASIS): Cross-sectional MRI Data in Young, Middle Aged, Nondemented, and Demented Older Adults
Open accessAbstract
The Open Access Series of Imaging Studies is a series of magnetic resonance imaging data sets that is publicly available for study and analysis. The initial data set consists of a cross-sectional collection of 416 subjects aged 18 to 96 years. One hundred of the included subjects older than 60 years have been clinically diagnosed with very mild to moderate Alzheimer's disease. The subjects are all right-handed and include both men and women. For each subject, three or four individual T1-weighted magnetic resonance imaging scans obtained in single imaging sessions are included. Multiple within-session acquisitions provide extremely high contrast-to-noise ratio, making the data amenable to a wide range of analytic approaches including automated computational analysis. Additionally, a reliability data set is included containing 20 subjects without dementia imaged on a subsequent visit within 90 days of their initial session. Automated calculation of whole-brain volume and estimated total intracranial volume are presented to demonstrate use of the data for measuring differences associated with normal aging and Alzheimer's disease.
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OASIS-3 is a longitudinal dataset that integrates multiple modalities including neuroimaging, clinical biomarkers, and cognitive assessment.
“Another typical database is the longitudinal dataset called OASIS-3, which integrates multiple modalities [2], including neuroimaging, clinical biomarkers, and cognitive assessment.”
From A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis (2024) · cites this paper as [2]
OASIS-3 primarily investigates the progression of Alzheimer's disease in 1378 individuals.
“This dataset primarily investigates the progression of AD in 1378 individuals.”
From A Comprehensive Review on Synergy of Multi-Modal Data and AI Technologies in Medical Diagnosis (2024) · cites this paper as [2]
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- Authors
- Marcus, D. S., Wang, T. H., Parker, J., Csernansky, J. G., Morris, J. C., & Buckner, R. L.
- Affiliations
- 1Washington University
- Harvard University (US)
- Howard Hughes Medical Institute (US)
- Venue
- Journal of Cognitive Neuroscience
- Publisher
- MIT Press
- Published
- 2007-09-01
- Volume
- 19
- Issue
- 9
- Pages
- 1498-1507
- ISSN
- 0898-929X (ISSN-L)
- 1530-8898
- OpenAlex
- W2150534249
- Cited by
- 2,163
- References
- 48
- Citations by year
- 2026: 217 · 2025: 270 · 2024: 231 · 2023: 177 · 2022: 165 · 2021: 158 · 2020: 126 · 2019: 113 · 2018: 105 · 2017: 96 · 2016: 66 · 2015: 78 · 2014: 66 · 2013: 72 · 2012: 70
- FWCI
- 19.30
- Type
- journal article
- Language
- en
- Open access
- green
- nrs.harvard.edu
- Licence
- cc-by
- Locations
- Journal of Cognitive Neuroscience (publishedVersion)
- PubMed (publishedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- Funders
- National Institute on Aging (R01AG021910, P50AG005681, P01AG003991)
- National Institute of Mental Health (P20MH071616)
- National Center for Research Resources (RR16594, RR 14075, P41RR014075, R01RR016594)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Keywords
- Alzheimer's disease, dementia, normal aging, brain structure, T1-weighted imaging, total brain volume, intracranial volume, older adults, OASIS
- MeSH terms
- Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Aging, Brain, Brain Mapping, Cross-Sectional Studies, Dementia, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Sex Factors, Reproducibility of Results
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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