Synthetic kidney ASL data with respiratory motion was generated using models from the XCAT phantom and matching recommendations for in-vivo acquisitions. Both pCASL and PASL datasets with 1 M0 and 25 control-label pairs were created and analysed using an in-house developed processing pipeline including registration, manual segmentation, calculation of mean perfusion-weighted image and perfusion map. The registration performed well on the synthetic data and the perfusion maps yielded good cortex/medulla contrast. The presented method allows a wide range of parameter choices for creating synthetic ASL datasets valuable for testing processing pipelines and comparing them across research and clinical imaging centres.
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