Deep learning (DL) has recently been proven to be effective in addressing the safety concerns of Gadolinium-based Contrast Agents (GBCAs). Recent studies have shown that DL-based algorithms are able to reconstruct contrast-enhanced MRI images with only a fraction of the standard dose. This work investigates the feasibility of improving the performance of such DL algorithms using multi-contrast MRI data, combined with an unsupervised anomaly detection based attention mechanism.
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