English(EN) Probabilistic Modeling of Multi-rater Medical Image Segmentation for Diversity and Personalization

研究人员开发 ProSeg 用于多样化和个性化的医学图像分割

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-05 04:00

研究人员开发了 ProSeg，一种用于多评分者医学图像分割的新型概率建模方法。该方法通过引入潜在变量来捕捉专家偏好和边界不确定性，解决了评分者间变异性和病灶边界模糊的挑战。ProSeg 能够生成多样化且个性化的分割输出，在鼻咽癌和肺结节数据集上取得了最先进的性能。 AI

影响通过考虑评分者变异性，引入了一种提高医学图像分割准确性和可解释性的新方法。

排序理由这是一篇详细介绍医学图像分割新概率建模方法的学术论文。

AI 生成摘要 · Google Gemini · 来自 1 个来源。我们如何撰写摘要 →

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arXiv cs.CV TIER_1 English(EN) · Ke Liu, Shangde Gao, Yichao Fu, Shuaike Shen, Shangqi Gao, Chunhua Shen · 2026-05-05 04:00

多评分者医学图像分割的概率建模以实现多样性和个性化

arXiv:2512.00748v2 Announce Type: replace Abstract: Lesion segmentation is inherently influenced by imaging uncertainty, arising from ill-defined lesion boundaries and inter-observer variability in diagnosis. To address this challenge, previous works formulated the multi-rater me…