Keywords: PET/MR, Arterial spin labelling, perfusion imaging, PET, dataset, open source
Motivation: Create a publicly available dataset combining non-invasive ASL perfusion imaging and simultaneous 15O-H2O PET/MRI to facilitate research replication, deep learning model training, and advance open science initiatives.
Goal(s): Introduce and validate a dataset comparing ASL perfusion imaging against gold-standard 15O-H2O PET/MRI to improve reproducibility studies and support research in healthy controls and Moyamoya patients.
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Approach: Imaging data from 70 healthy controls and 50 Moyamoya patients using 3T PET/MRI covered structural, DWI, ASL perfusion, DSC, and 15O-H2O PET data. Data were harmonized and validated per BIDS specifications.
Results: The dataset passed BIDs validation and included demographics, raw data, BIDS-compliant metadata, and derivatives(CBF maps).
Impact: This dataset can significantly advance neuroimaging research by enabling reproducibility studies, validating ASL imaging against PET, and supporting artificial intelligence approaches. It provides a critical resource for scientists, clinicians, and data-driven innovations.
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