ArticleMagnetic resonance in medicine2026
From Offline to Inline Without Pain: A Practical Framework for Translating Offline MR Reconstructions to Inline Deployment Using the Gadgetron Platform.
Article in Magnetic resonance in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Online image reconstruction via Multiple Orthogonal Reference Sensitivity Encoding (MORSE).Magma (New York, N.Y.) · 2026Article
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Authors and funding
27 authors.
Funding
Abstract
purposeTo develop and validate a practical, open-source framework to overcome common issues in inline deployment of established offline MR reconstruction, including (1) scan disruption from lengthy reconstructions, (2) limited support for multi-scan input reconstructions, (3) needs to adapt scripts for different raw-data formats, and (4) limited guidance and experience in retaining scanner reconstructions and applying scanner-based post-processing to custom-reconstructed images.
methodsThe framework builds upon the Gadgetron platform as implemented on Siemens scanners and includes: (1) a general input converter to convert Gadgetron-used ISMRMRD format raw into a Siemens format raw structure, facilitating reuse of code; (2) an asynchronous trigger-and-retrieve mechanism enabling long custom reconstructions without delaying scanner processes; (3) resource-aware scheduling for parallel execution of reconstructions; (4) integrated file management to support multi-scan inputs; and (5) preservation of scanner-based reconstructions and post-processing. The framework was validated on 2 Siemens scanners for SENSE, AlignedSENSE, and NUFFT reconstructions, and in a large-cohort study.
resultsMinimum code modification for inline deployment was demonstrated, and all reconstructions were successfully executed inline without disrupting scanner workflows. Images were retrieved automatically via retrieval scans or manually via retro-reconstruction, with scanner-based post-processing applied to custom outputs. Multi-sequence reconstructions were executed using GPU-aware scheduling, confirming feasibility for large-scale applications. In 480 examinations, inline reconstructions were retrieved in 99% of cases without disruptions.
conclusionThe framework lowers the technical barrier to inline deployment of offline reconstructions, enabling robust, scalable, and post-processing-compatible integration. It is openly available with documentation and demonstration cases to support reproducibility and community adoption.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.