Abstract #0422

Fully Automated Online Reconstruction, Registration, and Analysis Pipeline for 3D Magnetic Resonance Fingerprinting

Andrew Dupuis¹, Rasim Boyacioglu¹, Yong Chen¹, Michael Hansen², Kelvin Chow³, Chaitra Badve⁴, Dan Ma¹, and Mark Griswold¹

¹Biomedical Engineering, Case Western Reserve University, Cleveland, OH, United States, ²Microsoft Research, Redmond, WA, United States, ³Siemens Medical Solutions USA, Inc., Chicago, IL, United States, ⁴Radiology, University Hospitals, Cleveland, OH, United States

Synopsis

Keywords: MR Fingerprinting/Synthetic MR, Quantitative Imaging, Gadgetron, Brian Tumor, MNI, FSL, Docker, Automated, RegistrationIn this study, to overcome some of the clinical integration issues of MRF, we present a fully automated online reconstruction and post-processing pipeline for 3D-MRF where the quantitative maps and custom reports are returned to the scanner in real time. The whole pipeline is hosted in a Kubernetes cluster which includes Gadgetron, FSL and other custom tools in discrete Docker images. To illustrate the capability of the pipeline, 3D-MRF raw datasets of healthy and brain tumor patient datasets are reconstructed in a cloud-based Gadgetron, registered to MNI space using FSL and analyzed to compare with population based regional maps.

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.