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IPOR 2026: International Conference on Imaging Processing for Medical-Oriented Recognition

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截稿日期:
2026-09-18 还有 3 天
通知日期:
2026-10-23
会议日期:
2026-11-27
会议地点:
Kuala Lumpur, Malaysia
届数:
浏览: 5832   关注: 0   参加: 0

会伴指数 (CP-I)

42.7 / 100
全站第 3,955 名 / 共 5,682 个会议 · 前 70%

生物信息学与健康信息学 第 113 / 183 计算机视觉与模式识别 第 201 / 244

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%)
30
社区关注 (10%)
10
资料公开度 (15%)
55

用到的输入: 有据可查的届次：2 · 过去 24 个月打开过本页的研究者：3 人

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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 1.1 · 算于 2026-09-15

征稿

IPOR 2026 (International Conference on Imaging Processing for Medical-Oriented Recognition) is an academic conference held in Kuala Lumpur, Malaysia on 2026-11-27. The paper submission deadline is 2026-09-18. Acceptance notifications are sent on 2026-10-23.

The topics of interest for submission include, but are not limited to: Biomedical Imaging Medical Image Acquisition and Reconstruction Techniques; 3D and 4D Medical Image Processing; Multimodal Imaging Fusion (MRI, PET, CT, Ultrasound); Deep Learning in Medical Imaging; AI-Assisted Radiological Diagnosis, etc. Optics-Enhanced Biomedical Imaging and Signal Processing Optical Coherence Tomography (OCT) and Applications; Optical Signal Processing in Laser-Assisted Surgery; Deep Learning for Optical Image Interpretation; Machine Learning for Spectral Signal Classification; AI-Enhanced Optical Flow in Biomedical Video Analysis, etc. Biomedical Signal Processing Biomedical Signal Acquisition and Instrumentation; AI and Machine Learning for Biomedical Signal Analysis; Real-Time Signal Processing for Wearable Devices; Non-Invasive Monitoring and Analysis Techniques; Biomedical Signal Compression and Encryption, etc. Intelligent Diagnosis and Clinical Applications AI Algorithms for Disease Detection, Classification, Staging, and Diagnosis; Models for Disease Progression Prediction, Prognostic Assessment, and Efficacy Monitoring; Large Language Models and Vision-Language Models Applications; Innovation and Application of Deep Learning Models; Generative AI Applications, etc.
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