Author

Michael Götz

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Preprint Aug 2026

A Modular Agent for Reliable and Auditable Spatial Relation Verification in CT Scans

This work presents a modular medical imaging agent for binary spatial relation verification in axial CT slices using explicit modular spatial verification stages, and suggests that explicit modular spatial verification can serve as a promising building block for future report-oriented medical imaging agents.

S. Abel, Heiko Hillenhagen, Michael Götz et al. · 0 citations

Jul 2026

Towards Practical Algorithm Selection for Unsupervised Domain Adaptation in Medical Imaging

This work proposes a label-free criterion that jointly selects the algorithm and hyperparameters for UDA, and achieves better selection performance than other methods and remains effective across different algorithm pools.

Yi Xiong, L. Gallée, D. Wolf et al. · arXiv.org · 0 citations

Preprint Aug 2026

How Far from Clinical Deployment? Evaluating the Complete Unsupervised Domain Adaptation Pipeline in Medical Imaging

This study finds that a capable adapted model usually exists, but identifying it without target labels is difficult: the validator-selected models leave a large and structural target performance gap to the best available one, with no evaluated validator consistently reliable.

Yi Xiong, L. Gallée, D. Wolf et al. · 1 citation