Baochang Zhang

Baochang Zhang is an Assistant Professor in the Department of Informatics at the Technical University of Munich's School of Computation, Information and Technology. He is affiliated with the Chair of Computer Applications in Medicine (Prof. Navab) at the Garching campus, specializing in medical image analysis and AI-driven healthcare solutions.

His research focuses on Medical Image Analysis with emphasis on vascular structures, including:

• Deep learning for low-dose CT denoising and X-ray angiography processing
• Multi-modal fusion techniques for cognitive impairment prediction
• Real-time surgical guidance systems for endovascular procedures
• Self-supervised learning frameworks for vessel segmentation

Analysis of his 15 most recent publications (2019-2025) reveals a strong trajectory in solving clinical imaging challenges through innovative AI methods. His work consistently bridges computer vision and clinical applications, with increasing focus on zero-shot learning, domain adaptation, and surgical robotics integration since 2022. Key trends include replacing traditional segmentation with diffusion models and addressing missing data in multi-modal clinical datasets.

No scientific awards were documented in the provided materials.

While no formal advisees are listed in the scraped data, his lab appears to focus on translational medical AI projects with strong industry and clinical partnerships. The publications suggest active grant funding in EU medical technology initiatives, particularly for intraoperative imaging systems and neurodegenerative disease prediction tools.

Zhang leads research within TUM's medical imaging group under Prof. Navab, likely contributing to the CAMP (Computer Aided Medical Procedures) Lab ecosystem. His team develops clinical decision support systems with emphasis on real-time vascular analysis during interventions.