Author

J. Kleesiek

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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 Sep 2026

BiCC: Bidirectional Connected-Component Loss for Instance-Aware Segmentation

Common segmentation losses aggregate errors voxel-wise, so lesions influence the objective in proportion to their volume, giving small but clinically critical lesions disproportionately little weight. Instance-aware losses aim to address this mismatch by assigning each lesion its own term. However, blob loss and CC-Dic...

Luc Bouteille, F. Jonske, J. Kleesiek et al. · 0 citations

Preprint Aug 2026

Case2Flow: Bridging Patient Cases and Guideline Flowcharts through Multimodal Retrieval

Case2Flow is introduced, a task designed to retrieve the most relevant guideline flowchart for a given patient case from a collection of guideline documents and CRISP, a training-free scoring method that sharpens late-interaction retrieval by suppressing uninformative patches, discounting ambiguous token matches, and i...

Jia-Le Wei, Yu-Fan Chen, Alexander Jaus et al. · 0 citations