Keywords: Machine Learning/Artificial Intelligence, Motion CorrectionPeriodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) MRI technique enables the correction of motion artifacts resulted from patient motions in a scanner. Undersampling the blades can increase data acquisition speed and reduce potential motions caused by pains in a short time but may degrade image quality. Deep neural networks may support the blade reconstruction with undersampled data but motion patterns are difficult to be acquired for building a training dataset. To avoid the acquisition of training data, this abstract proposes an untrained neural network-based PROPELLER reconstruction technique to enhance image quality with undersampled blades.
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