• Algorithms for medical image segmentation, registration, reconstruction, etc. (医学图像分割、配准、重建等算法)
• Intelligent annotation of images and construction of high-quality datasets (影像智能标注与高质量数据集构建)
• Application optimization of medical multimodal large models and basic models (医学多模态大模型与基础模型应用优化)
• Generative AI, data augmentation, and domain generalization (生成式 AI、数据增强与域泛化)
• Research in brain science and brain-computer interface direction (脑科学、脑机接口方向研究)
• Research on explainability and uncertainty of medical AI algorithms (医学 AI 算法可解释性与不确定性研究)
• Image-guided therapy, application, and clinical validation (影像引导治疗、应用与临床验证)
• Quantitative analysis and biomarker mining (定量分析与生物标志物挖掘)
  

Medical image and signal processing is a key intersection field between medicine and engineering. Technologies such as image segmentation, registration, and multimodal fusion provide important support for disease-assisted diagnosis and quantitative evaluation. However, it still faces practical challenges such as scarce labeling, domain shift, and difficulty in clinical implementation. This special topic is aimed at researchers from the fields of biomedical engineering, medicine, and computer science. It focuses on method innovation and application transformation, shares cutting-edge achievements, conducts discussion on viewpoints, and aims to promote interdisciplinary exchanges, stimulate new ideas, and facilitate the iterative development and practical application of medical image and signal analysis technologies.