Keywords: Arterial Spin Labelling, Arterial spin labelling, Deep Learning, Denoising
Motivation: Arterial spin labeling (ASL) typically requires repeated measurements due to low SNR and/or transit delay sensitivity, resulting in long scan time.
Goal(s): To explore the feasibility of ASL measurement with a single-repetition.
Approach: To take advantage of recent technical advances, deep learning denoising and velocity-selective ASL approaches are combined to explore the feasibility of obtaining reliable perfusion measurement with considerable less scan time, in the extreme case, using one single repetition of ASL scan.
Results: Our preliminary results demonstrated the feasible of whole-brain ASL measurement with a single repetition. This new method will be investigated further.
Impact: The method proposed in this study will enable accurate ASL perfusion measurement with significant reduction of scan time, making ASL potentially an additional diagnostic tool in acute perfusion imaging applications where scan time is extremely precious.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords