Author

C. Seibold

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#machine learning Jul 2025

Automatic Fine-grained Segmentation-assisted Report Generation

ASaRG proposes to fuse intermediate features and fine-grained segmentation maps created by specialist radiological models into LLaVA's multi-modal projection layer via simple concatenation, an extension of the popular LLaVA architecture that aims to tackle both of these problems.

F. Jonske, C. Seibold, Osman Alperen Koras et al. · arXiv.org · 1 citation

Review Open access Oct 2026

Fluent but not fail-safe: machine-translated radiology reports still need expert review

Cross-border care, teleradiology, and international referral pathways increasingly require radiology report translation, but isolated mistranslations may alter clinical meaning. We evaluated German-to-English machine translation of radiology reports and correction-based localization of text requiring review. In this re...

C. Seibold, Timo Leichenich, Patrick Stein et al. · European Radiology Experimen... · 0 citations