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Author

L. Müller

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4 papers indexed here

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Open access Sep 2026

Deep Learning-Based Image Reconstruction in Ultra-High-Resolution CT Venography for Improved Visualization of Cerebral Venous Drainage.

PURPOSE To evaluate the diagnostic confidence and image quality of deep-learning-enhanced ultra-high-resolution CT venography (CTV) in venous neurovascular imaging, compared with hybrid iterative reconstruction of ultra-high-resolution CT datasets and normal-resolution CTV. METHODS This retrospective, single-center s...

Sebastian Steinmetz, Anna-Luisa Grebe, M. Kondova et al. · 0 citations
Open access Aug 2026

Measurements of Liver and Bone Marrow Proton Density Fat Fraction in the Setting of Ferumoxytol-Enhanced MRI.

BACKGROUND Proton density fat fraction (PDFF) is typically measured using confounder-corrected, multi-echo, gradient-recalled-echo chemical-shift-encoded (CSE)-MRI. Ferumoxytol, an iron-based MRI contrast agent, increases liver and bone marrow (BM) R2*, a major confounder of PDFF. PURPOSE To assess the impact of feru...

L. Müller, Srijyotsna Volety, J. Grunz et al. · 1 citation
Open access Aug 2026

Augmenting Head and Neck Multidisciplinary Tumor Board Recommendations With Locally Run Large Language Models: Prospective Evaluation of Real-World Implementation

The data demonstrate that the integration of LLMs in today’s MDT workflow is feasible and may benefit the quality of decision-making in specific cases, and suggests that more advanced local models may offer safe, rapid, and cost-effective support for MDT decision-making.

C. Buhr, L. Müller, D. Pinto dos Santos et al. · 0 citations
Open access Jul 2026

Deep learning-based detection of acute pancreatitis on abdominal contrast-enhanced CT

DL enabled accurate CECT-based identification of AP in this retrospective multicenter cohort, with performance maintained in an independent external dataset, and showed promising performance for CECT-based acute pancreatitis detection.

Oleksandra Seidel, M. Theis, Sebastian Nowak et al. · 0 citations

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