Keywords: Machine Learning/Artificial Intelligence, AI/ML Image Reconstruction
Motivation: Susceptibility-weighted imaging (SWI) at ultra-high field 7T is a powerful tool for evaluating a wide range of pathology, but has long acquisition time.
Goal(s): To investigate the diagnostic performances of highly accelerated 7T SWI using multi-scale hybrid CNN-Transformer Network (MACT-Net).
Approach: The diagnostic performances of the MSCT-Net reconstructed images for identifying swallow tail sign (STS) and distinguishing Parkinson’s disease (PD) patients from healthy controls were evaluated on an independent PD cohort.
Results: With a 6-8-times acceleration, MSCT-Net showed comparable diagnostic performance to the fully sampled 7T SWI for discriminating PD from healthy controls using the bilateral STS evaluation score.
Impact: The potentially reduced scan time with MSCT-Net offers new possibilities for widely adoption of 7T SWI in clinical brain imaging. Furthermore, the approach has the potential to guide design of reconstruction models for other high-resolution 7T MRI data.
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