Keywords: CEST & MT, Data AnalysisZ-spectrum acquired under ultra-high field (> 3T) features stronger and better isolated CEST peaks than those under 3T. But from imaging aspect, 3T scanners perform better and are clinically accessible. Herein, we built a deep neural network (DNN) for predicting Z-spectrum under higher B0 from the corresponding measurement at 3T. The network was trained by 10 million Z-spectra calculated from Bloch-equation models. Simulations with various B0 shifts and noise suggested that 3T Z-spectra could be rapidly and accurately transformed to those under 7T or 9.4T. This network may help improve signal extraction and interpretation of CEST data acquired at 3T.
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