The estimation of intravoxel distributions of T2 values based on multi-echo MR data is a challenging task. Interestingly, the information above is quite useful to detect damage on brain tissue, e.g. to estimate myelin-water-fraction changes associated with demyelination processes. Currently available methods typically require a long train of echoes, which are not always feasible to acquire. In this work we tackle this problem using state-of-the-art supervised learning convolutional networks to build a robust prediction model on very limited data ( 5 echoes and 4 TR). The methodology identifies myelin abnormalities in a rodent model of a neurological disorder with demyelination.
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