In 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.
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Dupuis et al. (2024) studied this question.
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