{"ID":2843287,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.08046","arxiv_id":"2511.08046","title":"ProSona: Prompt-Guided Personalization for Multi-Expert Medical Image Segmentation","abstract":"Automated medical image segmentation suffers from high inter-observer variability, particularly in tasks such as lung nodule delineation, where experts often disagree. Existing approaches either collapse this variability into a consensus mask or rely on separate model branches for each annotator. We introduce ProSona, a two-stage framework that learns a continuous latent space of annotation styles, enabling controllable personalization via natural language prompts. A probabilistic U-Net backbone captures diverse expert hypotheses, while a prompt-guided projection mechanism navigates this latent space to generate personalized segmentations. A multi-level contrastive objective aligns textual and visual representations, promoting disentangled and interpretable expert styles. Across the LIDC-IDRI lung nodule and multi-institutional prostate MRI datasets, ProSona reduces the Generalized Energy Distance by 17% and improves mean Dice by more than one point compared with DPersona. These results demonstrate that natural-language prompts can provide flexible, accurate, and interpretable control over personalized medical image segmentation. Our implementation is available online 1 .","short_abstract":"Automated medical image segmentation suffers from high inter-observer variability, particularly in tasks such as lung nodule delineation, where experts often disagree. Existing approaches either collapse this variability into a consensus mask or rely on separate model branches for each annotator. We introduce ProSona,...","url_abs":"https://arxiv.org/abs/2511.08046","url_pdf":"https://arxiv.org/pdf/2511.08046v1","authors":"[\"Aya Elgebaly\",\"Nikolaos Delopoulos\",\"Juliane Hörner-Rieber\",\"Carolin Rippke\",\"Sebastian Klüter\",\"Luca Boldrini\",\"Lorenzo Placidi\",\"Riccardo Dal Bello\",\"Nicolaus Andratschke\",\"Michael Baumgartl\",\"Claus Belka\",\"Christopher Kurz\",\"Guillaume Landry\",\"Shadi Albarqouni\"]","published":"2025-11-11T09:50:36Z","proceeding":"cs.CV","tasks":"[\"cs.CV\",\"cs.AI\"]","methods":"[]","has_code":false}