Abstract #4352

Application-specific structural brain MRI harmonization

Lijun An^1,2,3, Pansheng Chen^1,2,3, Jianzhong Chen^1,2,3, Christopher Chen⁴, Juan Helen Zhou², and B.T. Thomas Yeo^1,2,3,5,6

¹Department of Electrical and Computer Engineering, National University of Singapore, Singapore, Singapore, ²Centre for Sleep and Cognition (CSC) & Centre for Translational Magnetic Resonance Research (TMR), National University of Singapore, Singapore, Singapore, ³N.1 Institute for Health & Institute for Digital Medicine (WisDM), National University of Singapore, Singapore, Singapore, ⁴Department of Pharmacology, National University of Singapore, Singapore, Singapore, ⁵NUS Graduate School for Integrative Sciences and Engineering, National University of Singapore, Singapore, Singapore, ⁶Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, United States

Synopsis

We propose a flexible application-specific harmonization framework utilizing downstream application performance to regularize the harmonization procedure. Our approach can be integrated with various deep learning models. Here, we apply our approach to the recently proposed conditional variational autoencoder (cVAE) harmonization model. Three datasets (ADNI, N=1735; AIBL, N=495; MACC, N=557) collected from three different continents were used for evaluation. Our results suggest our approach (AppcVAE) compares favorably with ComBat (named for “combating batch effects when combining batches”) and cVAE for improving downstream application performance.

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.