BIBE-MIAID' 25: Medical Image Analysis and Intelligent Diagnosis
Medical image analysis and intelligent diagnosis is an important branch of medical science and technology that uses advanced image processing, computer vision, deep learning and big data analysis technologies to accurately and efficiently interpret and diagnose medical images, greatly improving the accuracy and efficiency of medical diagnosis. The importance of this field is self-evident, as it not only helps doctors to detect diseases faster and more accurately and to formulate more timely and effective treatment plans for patients, thereby improving the quality of medical care and the survival rate of patients, but also enables more patients to receive timely and effective treatment recommendations through the assisted diagnosis of intelligent technologies, thereby improving the overall level and accessibility of medical services.
BIBE-MIAID' 25 topics include but not limited to：
1. Medical imaging
2. Lesion identification and localisation
3. Early detection of disease
4. Multimodal fusion and analysis
5. Telemedicine services
6. Prognostic assessment and management
Session Chair
Jinyu Wen
Associate Researcher, Guangzhou University
Bio： Dr Wen is currently an associate researcher at the School of Computer Science and Cyber Engineering, Guangzhou University. She focuses on applied research at the intersection of computer technology and medicine, especially in the areas of computer vision, deep learning, AI medical image analysis and intelligent assisted diagnosis, and is committed to applying advanced AI technologies to medical image analysis and disease prediction. She has published 15 academic papers, including 10 papers as first author in top international journals such as IEEE Transactions on Image Processing, IEEE Transactions on Multimedia, and IEEE Transactions on Biomedical Engineering.
Speakers
Yang Li
Lecturer
College of Computer Science and Engineering, Shandong University of Science and Technology, China
Research Interests: Machine Learning, Medical Image Processing, Deep Learning, Artificial Intelligence, Coal Body Pore Fracture Analysis
Speech Title: Research on PET-MRI image fusion and key technology for brain tumour diagnosis
Ziduo Yang
Lecturer
College of Information Science and Technology, Jinan University, China
Research Interests: AI Medical Image Analysis, AI Drug Design, AI Materials Design, Medical Informatics, Bioinformatics, Chemoinformatics, Materials Informatics
Speech Title: Advances in labour ultrasound AI research