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Open access Sep 2026

A deep learning framework for automated quantification of peripheral nerve lesions in MR neurography

Magnetic resonance neurography (MRN) enables high-resolution visualization of peripheral nerves, yet quantitative analysis of intraneural lesion burden remains limited by manual, observer-dependent workflows. We propose a deep learning-based framework for automated segmentation and quantitative characterization of peri...

N. Beste, Clara Raudonat, M. Fesselier et al. · 0 citations
Aug 2026

Fast and robust q-space trajectory imaging using voxel-wise multilayer perceptrons for parameter estimation.

Q-space trajectory imaging (QTI) provides promising markers of tissue microstructure, but clinical translation requires shorter acquisitions, faster analysis, and more robust parameter estimation at high spatial resolution. To address these barriers, we trained a voxel-wise multilayer perceptron (MLP) to infer QTI-deri...

Oliver Gödicke, Jin-Yang Yu, F. Laun et al. · 0 citations

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