MICAD 2025

The 6^th International Conference on Medical Imaging and Computer-Aided Diagnosis (MICAD 2025) was held in London, UK, from November 19 to 21, 2025.

MICAD 2025 attracted broad international participation, with approximately 100 attendees from more than 40 countries and regions joining the conference both onsite and online. A total of 160 paper submissions were received, reflecting the strong research interest and active engagement within the medical imaging and computer-aided diagnosis community.

The conference program featured 9 speakers and over 60 oral and poster presentations. The presented works covered a wide range of topics across medical imaging technologies, computational methods, and clinical applications, providing opportunities for in-depth academic exchange and discussion.

By bringing together researchers, clinicians, and practitioners from diverse backgrounds, MICAD 2025 served as an effective platform for sharing recent advances, discussing emerging challenges, and exploring future research directions in medical imaging and computer-aided diagnosis.

Group photos of MICAD 2025

  

Keynote Speakers of MICAD 2025

Prof. Junzhou Huang from The University of Texas at Arlington, United States delivered his keynote speech titled "Multimodal Large Language Models for Computational Pathology".

Prof. Jinman Kim from The University of Sydney, Australia delivered his keynote speech titled "Multi-modal AI for Biomedical Image Analysis and Visualisation".

Prof. Gang Li from University of North Carolina at Chapel Hill, United States delivered his keynote speech titled "Deep Learning Models for Pediatric Neuroimage Analysis".

Prof. Yiyu Shi from University of Notre Dame, United States delivered his keynote speech titled "Can Quantum Computers Help Medical Image Computing?".

Prof. Greg Slabaugh from Queen Mary University of London, UK delivered his keynote speech titled "From Multimodal Fusion to Foundation Models and Digital Twins in Medical AI".

Prof. Tom Vercauteren from King's College London, UK delivered his keynote speech titled "AI-defined hyperspectral surgical imaging: From spectral data to surgical insight".

Invited Speakers of MICAD 2025

Assoc. Prof. Mingchen Gao from University at Buffalo, SUNY, United States delivered her invited speech titled "Label-Efficient Learning for Medical Image Analysis with Partially Labeled Data".

Prof. Mingwu Jin from University of Texas at Arlington (UTA), United States delivered his invited speech titled "Generative models for denoising and super-resolution of low-dose X-ray computed tomography (CT)".

Prof. Jin Tae Kwak from Korea University, Korea delivered his invited speech titled "Computational pathology in the era of large-scale AI models".