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Abstract #4935

MR-Neurography with a Fully Automated Nerve Segmentation Workflow

Andreas Holl1, Shadi Tashakori1, Ben Wilhelm-Feldbusch1, Marco Reisert1, Alexander Rau2, Maxim Zaitsev1, and Sebastian Littin1
1Division of Medical Physics, Department of Diagnostic and Interventional Radiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany, Freiburg, Germany, 2Department of Neuroradiology, University Medical Center Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany, Freiburg, Germany

Synopsis

Keywords: Peripheral Nerves, Neurography, Automated Segmentation

Motivation: There is no established workflow for an automated segmentation of peripheral nerves for MR-Neurography (MRN). Existing methods provide poor nerve visibility.

Goal(s): Provide an improved workflow for cross-patient MRN for healthy and pathologic peripheral nerves, enabling automated nerve-segmentation and improving precision of clinical applications.

Approach: 3D T1w-FLASH and DWI SE-EPI sequences were optimized for MRN. A fully automated nerve-segmentation algorithm for healthy and pathologic nerves was developed.

Results: Our workflow delivers ultra-high resolution MRN-images with improved nerve visibility and a fully automated identification and segmentation of peripheral nerves.

Impact: The developed workflow enhances clinical MR-Neurography by improving image quality, automating the identification and segmentation of nerves, rendering diagnoses more precise and efficient, and allowing cross-patient application with both healthy and pathological peripheral nerves.

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Keywords