| Description
| This course explores intelligent medical imaging and biomedical signal processing techniques, along with their analytical and interpretive methods in clinical applications. It covers fundamental concepts of medical image and signal processing, including the principles and techniques of image enhancement, noise suppression, filtering, edge detection, image segmentation, and registration, as well as biomedical signal preprocessing and feature extraction methods. Building upon this foundation, the course further introduces the application of machine learning and deep learning to medical image classification, detection, and segmentation. It also addresses model evaluation metrics, model statistics, interpretability analysis, and the potential and limitations of image–text multimodal models in assisting clinical interpretation. In addition, topics such as data ethics, privacy governance, and sovereign AI are discussed, enabling students to understand the challenges of deploying medical ima
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