{"ID":2835860,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2511.22236","arxiv_id":"2511.22236","title":"Bridging 3D Deep Learning and Curation for Analysis and High-Quality Segmentation in Practice","abstract":"Accurate 3D microscopy image segmentation is critical for quantitative bioimage analysis but even state-of-the-art foundation models yield error-prone results. Therefore, manual curation is still widely used for either preparing high-quality training data or fixing errors before analysis. We present VessQC, an open-source tool for uncertainty-guided curation of large 3D microscopy segmentations. By integrating uncertainty maps, VessQC directs user attention to regions most likely containing biologically meaningful errors. In a preliminary user study uncertainty-guided correction significantly improved error detection recall from 67% to 94.0% (p=0.007) without a significant increase in total curation time. VessQC thus enables efficient, human-in-the-loop refinement of volumetric segmentations and bridges a key gap in real-world applications between uncertainty estimation and practical human-computer interaction. The software is freely available at github.com/MMV-Lab/VessQC.","short_abstract":"Accurate 3D microscopy image segmentation is critical for quantitative bioimage analysis but even state-of-the-art foundation models yield error-prone results. Therefore, manual curation is still widely used for either preparing high-quality training data or fixing errors before analysis. We present VessQC, an open-sou...","url_abs":"https://arxiv.org/abs/2511.22236","url_pdf":"https://arxiv.org/pdf/2511.22236v1","authors":"[\"Simon Püttmann\",\"Jonathan Jair Sànchez Contreras\",\"Lennart Kowitz\",\"Peter Lampen\",\"Saumya Gupta\",\"Davide Panzeri\",\"Nina Hagemann\",\"Qiaojie Xiong\",\"Dirk M. Hermann\",\"Cao Chen\",\"Jianxu Chen\"]","published":"2025-11-27T09:02:02Z","proceeding":"cs.CV","tasks":"[\"cs.CV\"]","methods":"[]","has_code":false}