Keywords: Machine Learning/Artificial Intelligence, Arterial spin labelling, Noise reductionOptimized pseudo-Continuous Arterial Spin Labeling has been implemented at 7T. To achieve whole brain high-resolution (2mm isotropic) perfusion imaging at 7T, however, requires prolonged scan time with an increased number of segments. A deep learning (DL) model was trained to boost the signal-to-noise ratio (SNR) for a scan with fewer repetitions and thus a shorter scan time. The analysis of SNR and temporal SNR suggests that at least 3 repetitions are needed to make a high-SNR prediction comparable to the full scan without compromising quantification accuracy. With DL denoising, the original 12 mins scan can be finished in 4 min.
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