Given the very large number of individual datasets acquired in recent population imaging studies, it is becoming essential to automate data quality control (QC). Here we present an automated QC framework to assess diffusion MRI data both at the single subject and group levels. The QC metrics are derived through different stages of FSL’s pre-processing tools (TOPUP and EDDY). We show that using this framework, it is possible to distinguish between good and bad quality datasets and, importantly, identify subsets of the data that may need careful visual inspection. We hope this QC tool will help harmonisation efforts across sites/studies.
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