AISSLab Wins Best Workshop Paper Runner-Up Award at World-Leading MICCAI 2025 Conference
- AISSLab is thrilled to announce that our research team, led by Professor Mugahed A. Al-antari, has received the Best Workshop Paper Runner-Up Award at the 28th International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI 2025). The prestigious event was held from September 23-27 at the Daejeon Convention Center.
- MICCAI is globally recognized as one of the top-tier conferences in medical imaging and AI, attracting over 3,300 leading researchers, clinicians, and industry experts annually to share groundbreaking research.
- Representing AISSLab, Master's student Mukhlis Raza presented the award-winning paper at the 'Agentic AI for Medicine' workshop. The paper, titled "MedXpert-CAD: A Multimodal Multi-Agentic System for Clinical Imaging Analysis via Model Context Protocol LLM-Driven Agentic Workflows," has been published in Springer’s prestigious Lecture Notes in Computer Science (LNCS) series Paper Link.
MICCAI 2025’s ‘Best Workshop Paper Runner-Up Award’
- Our MedXpert-CAD system introduces a revolutionary clinical diagnosis framework that integrates intelligent AI agents with multiple types of medical data. Built on a foundation of Large Language Models (LLMs) and advanced vision encoders, the system functions as an intelligent medical chatbot, providing clinicians with evidence-based diagnostic support. It features four specialized agents a Supervisor, Online Search Agent, X-ray Expert, and Lumbar Spinal Stenosis (LSS) Expert that collaborate to analyze diverse medical images, from chest X-rays for respiratory diseases to complex spinal MRI data.
- This award validates Sejong University's leading role in developing intelligent AI for clinical applications and underscores AISSLab's contribution to creating rapid, interpretable, and scalable diagnostic workflows.
- Mukhlis Raza shared his experience, stating, “MICCAI 2025 was a meaningful opportunity to connect with outstanding researchers and industry leaders from around the world. The expert lectures provided deep insights into multimodal data, model bias, and the future of next-generation foundation models. This experience was incredibly valuable for my research journey.”
- Professor Mugahed A. Al-antari commented, “MedXpert-CAD merges Vision-Language Modeling (VLM) and Explainable AI (XAI) to enhance the efficiency and reliability of multi-medical image analysis. This achievement demonstrates our team’s dedication to developing a comprehensive AI diagnostic system that supports medical decision-making and serves as a stepping stone for the future of intelligent medicine. This award validates our team’s academic excellence and opens new possibilities for AI-driven medical innovation.”
- For more details please visit Sejong Newsroom
