UTE radial MRI methods are powerful tools for probing lung structure and function. However, the challenge in directly using this scheme for high-resolution lung imaging applications is the long breath-hold needed. While self-gating approaches that bin the data to different respiratory phases are promising, they do not allow the functional imaging of the lung and are often sensitive to bulk motion. The main focus of this work is to introduce a novel motion compensated manifold learning framework for functional and structural lung imaging. The proposed scheme is robust to bulk motion and enables high-resolution lung imaging in around 4 minutes.
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