Compressed Sensing with Self-Validation

Compressed sensing offers a capacity for accelerating data acquisition while keeping aliasing and noise effects subdued. Theories and experiences however are yet to establish a more robust guidance on random sampling, sparse model and non-linear solver, to help manage the challenge of using the technology in diagnostic MR. In this work we took a new angle and investigated the feasibility of introducing self-validation into compressed sensing MR. The goal is to assist fidelity assessment and improvement in practice with validation tests that can be automatically performed on any specific imaging instance itself, without requiring additional data or comparison references.

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.

Click here for more information on becoming a member.