会议信息

IPMI 2027: International Conference on Information Processing in Medical Imaging

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截稿日期:
2026-12-07 还有 44 天
通知日期:
2027-02-15
会议日期:
2027-06-27
会议地点:
Lake Stukely, Quebec, Canada
届数:
浏览: 33782   关注: 8   参加: 1
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会伴指数 (CP-I)

58.7 / 100
全站第 658 名 / 共 5,759 个会议 · 前 12%

生物信息学与健康信息学 第 13 / 184 计算机视觉与模式识别 第 23 / 246

学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
96
社区关注 (10%)
38
资料公开度 (15%)
55

用到的输入: 有据可查的届次:34 · 在会伴关注它的研究者:8 人 · 过去 24 个月打开过本页的研究者:8 人

公开资料里还缺: 历年录用率 (+4.5) · 最佳论文记录 (+2.3)
主办方认领本会议后,可直接在这一页补上;分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据,而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.2 · 算于 2026-10-24

征稿

IPMI 2027 (International Conference on Information Processing in Medical Imaging) is an academic conference held in Lake Stukely, Quebec, Canada on 2027-06-27. The paper submission deadline is 2026-12-07. Acceptance notifications are sent on 2027-02-15.

The Topics Following topics, and beyond, are welcome: ● Mathematical Foundations and Computational Methods Inverse problems and optimization theory • Computational anatomy and physiology • Geometric learning • Statistical and computational modeling • Quantum computing applications ● Image Formation and Reconstruction Image acquisition and reconstruction methods • Image registration, segmentation and fusion • Functional, diffusion and molecular imaging • Multidimensional, multimodality, multiscale problems ● Machine Learning and Intelligence Novel deep learning architectures and theory • Foundation models and multimodal learning • Generative modeling and synthesis • Transfer learning, domain adaptation and federated approaches • Uncertainty quantification and robust learning • Interpretable and causal learning methods ● Clinical Applications and Translation Image-guided interventions and surgery • Computer-aided diagnosis and treatment • Imaging genomics and omics integration • Digital twins and augmented reality applications ● Visualization and Human-AI Interaction Advanced visualization and immersive interfaces • Privacy-preserving and sustainable computing
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