Radial imaging is becoming increasingly popular due to its ability to support highly accelerated imaging. However, it is plagued by streak artifacts that often arise from undersampling which can lead to poor image quality. The problem is particularly acute in time resolved imaging where the need for high spatio-temporal sampling usually leads to large amount of streaks. In this work, we propose a method for separate spatial and temporal deep learning for streak artifact reduction. The utility of the method is demonstrated on free breathing time resolved volumetric DCE MRI acquired using the stack-of-stars trajectory.
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