Keywords: Machine Learning/Artificial Intelligence, BrainThe χ-separation method determines para- and diamagnetic susceptibility tissue compartments correlating to iron and myelin in the brain respectively. The method presupposes subject invariant relaxometry coefficients and compartments disregarding the changes in those parameters in disease or postmortem cases. We implement a biophysically informed autoencoder network developed for single subject use (BIOPHYSICSS-DL) to determine underlying biophysical model coefficients from individual datasets. We expand the current model with different combinations of relaxometry and susceptibility data to produce a self-calibrated χ separation method finding the network comparable to standard methods for iron and predicts myelin distribution more closely to ground truth histology.
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