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Author

Thomas Kuestner

3 papers indexed here

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Oct 2026

Uncertainty-aware auto-segmentation enables adaptive radiotherapy planning of liver metastases.

PURPOSE Despite remarkable auto-segmentation performance and growing clinical adoption, models frequently fail to generalize beyond the training distribution. Therefore, this study aimed to develop and validate an uncertainty-aware segmentation pipeline that yields high delineation accuracy for liver cancer patients an...

D. Langner, C. Gani, S. Boeke et al. · 0 citations
Open access Sep 2026

Variable flip angle T1 mapping for quantitative liver imaging at 0.55 T.

PURPOSE Investigating the feasibility of variable flip angle (VFA) T1 mapping for quantitative liver imaging at 0.55 T and evaluating the impact of RF spoiling correction and deep learning-based (DL) reconstruction on accuracy. METHODS A VFA protocol was developed and combined with DL reconstruction to improve quanti...

Majd Helo, M. Nickel, Thomas Kuestner · 0 citations
Open access Aug 2026

Memory-efficient image reconstruction using diffusion models for accelerated 3D non-Cartesian UTE imaging.

A novel, memory-efficient image reconstruction framework using score-based diffusion models tailored for highly undersampled 3D radial UTE acquisitions is proposed that enables robust and high-fidelity reconstructions from as few as 4000 spokes-representing up to 50 × undersampling relative to Nyquist.

Jonas Petersen, Stefan Sommer, Thomas Küstner · 0 citations

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