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AI for Medical Imaging
Deep learning for detection, classification, and segmentation across endoscopy, MRI, angiography, and multimodal imaging environments.
Dr. Furen Xiao (蕭輔仁)
National Taiwan University
The Intelligent Medical Device Laboratory develops clinically impactful technologies at the intersection of artificial intelligence, medical imaging, smart medical devices, and surgical innovation. Our mission is to build intelligent systems that improve diagnostic accuracy, enhance intervention precision, and support better patient outcomes.
Flagship international research programs
Students and researchers across medicine and engineering
Core pillars: AI, imaging, devices, and clinical translation
Our laboratory brings together expertise from medicine, computer science, medical imaging, electronics, biotechnology, and data science to develop next-generation medical technologies with real clinical impact.
Our work spans fundamental AI methods and clinically grounded medical device applications.
Deep learning for detection, classification, and segmentation across endoscopy, MRI, angiography, and multimodal imaging environments.
Collaborative AI training across institutions without sharing raw patient data, enabling safe and scalable multinational medical research.
AI-assisted surgical planning, image-guided intervention, and precision tools that improve workflow efficiency and treatment accuracy.
Embedded sensing systems, real-time physiological monitoring, and edge intelligence for next-generation medical device platforms.
The laboratory is guided by clinical and academic leadership with strong expertise in medicine, imaging, and translational healthcare innovation.
National Taiwan University
Taipei Hospital
Medicine, AI, imaging, and engineering
Our members work across neurosurgery, medical imaging, big data, biotechnology, veterinary science, electronics, law, respiratory science, and computer science.
Our current work combines federated learning, multimodal medical imaging, and clinically driven AI to address important healthcare challenges.
This multinational project develops a privacy-preserving federated AI framework for real-time detection and classification of colorectal polyps, colorectal cancer, and inflammatory bowel disease from endoscopic images.
This joint project integrates MRI and 3D rotational angiography to develop AI models for detecting and segmenting arteriovenous malformations and dural arteriovenous fistulas across multiple institutions.
Official laboratory activities, team gatherings, and academic event photographs.
The laboratory’s ongoing projects involve academic and clinical collaboration across Taiwan, Mongolia, and the United States, with contributions from major universities and hospitals.
Example partner institutions include National Taiwan University, National Taiwan University of Science and Technology, National Yang Ming Chiao Tung University, Taipei Medical University, Taipei Hospital, and the University of Illinois Chicago, alongside participating clinical centers.
Invite collaboration, student applications, and clinical partnerships through a clear and accessible contact section.