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Abstract #1962

Enabling Neurodesk workflows on the scanner console

Marshall Xu1, Steffen Bollmann2, Sommer Stefan3,4, Daniel Nanz4, Pim Pullens5, Kerrin J. Pine6, Kevin Chow7, Rainer Schneider8, Tobias Wuerfl8, Markus Barth2, and Daniel Guellmar9
1School of Electrical Engineering and Computer Science, The University of Queensland, Brisbane, Australia, 2The University of Queensland, Brisbane, Australia, 3Advanced Clinical Imaging Technology, Siemens Healthineers International AG, Zurich, Switzerland, 4Swiss Center for Musculoskeletal Imaging (SCMI) Balgrist Campus, Zurich, Switzerland, 5Ghent University Hospital, Ghent, Belgium, 6Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 7Cardiovascular MR R&D, Siemens Healthcare Ltd., Calgary, AB, Canada, 8Magnetic Resonance Imaging, Siemens Healthineers AG, Erlangen, Germany, 9Institute for Diagnostic and Interventional Radiology, Jena University Hospital, Jena, Germany

Synopsis

Keywords: Software Tools, Analysis/Processing

Motivation: This study addresses current challenges in image processing workflows, where manual exporting and importing MRI data limits real-time data processing and adds significant bottlenecks for clinical integration of analysis pipelines.

Goal(s): To enable streamlined, on-scanner processing with Neurodesk, enhancing accessibility to sophisticated imaging tools directly on MRI consoles.

Approach: To achieve this, we expanded Neurodesk’s capabilities to support the MRD format and Open Recon.

Results: Our results show successful development and testing of various containerized applications. Examples include brain extraction, segmentation, and anonymization tools, confirming the feasibility of direct deployment on MRI scanners for faster, consistent image processing workflows.

Impact: By enabling seamless integration of Neurodesk containers directly on the MRI scanner console, this work simplifies imaging pipeline deployment, reduces data analysis delays, and allows rapid image analysis ultimately supporting broader accessibility and clinical translation of advanced image processing pipelines.

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Keywords