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Abstract #5226

An open-source framework for cloud data processing from low-field scanners

Teresa Guallart-Naval1,2, Jose Miguel Algarin1,2, Fernando Galve1,2, John Stairs3, Michael Hansen3, and Joseba Alonso1,2
1Institute for Instrumentation in Molecular Imaging (i3M), CSIC, Valencia, Spain, 2Institute for Instrumentation in Molecular Imaging (i3M), Universitat Politècnica de València, Valencia, Spain, 3Microsoft Research, USA, Redmond, WA, United States

Synopsis

Keywords: Software Tools, Software Tools, accessible MRI, portable MRI, open-source, cloud data processing

Motivation: Advanced data processing tasks, such as model-based image reconstructions, require computational resources unavailable in many affordable and portable MRI systems.

Goal(s): The main goal is to release the first open-source framework for cloud data processing, compatible with the MaRCoS and MaRGE ecosystem developed for low-field MRI scanners.

Approach: We have upgraded MaRGE to integrate with Tyger, an open-source framework developed by Microsoft Research for remote signal processing.

Results: We have demonstrated a successful integration of Tyger with MaRGE, enabling standard and advanced image reconstruction in the cloud, and demonstrating also compatibility with a deep learning network.

Impact: This work connects affordable low-field MRI scanners to some of the most powerful computational cloud resources, where it shall be possible to execute strictly any tool that can be loaded into a Docker image.

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