Meeting Banner
Abstract #2900

Denoising single and multi-delay 3D pCASL using SWIN Transformer

Qinyang Shou1, Chenyang Zhao1, Xingfeng Shao1, and Danny JJ Wang1
1Laboratory of Functional MRI Technology (LOFT), Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA, United States

Synopsis

Keywords: Machine Learning/Artificial Intelligence, Machine Learning/Artificial IntelligenceWe developed a Transformer-based deep learning denoising model to improve the SNR for both single and multi-delay perfusion images acquired using 3D pseudo-continuous arterial spin labeling (pCASL). This method can significantly improve SNR (~2-fold) of the perfusion images without introducing bias for CBF and ATT quantification for both single-delay and multi-delay 3D pCASL. Further training and testing of this model on clinical datasets acquired on different vendor platforms is warranted.

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.

Keywords