Scribble-Supervised Medical Image Segmentation with Dynamic Teacher Switching and Hierarchical Consistency
IEEE 23rd International Symposium on Biomedical Imaging (ISBI) 2026
Hoang-Loc Cao
My research interests focus on Medical Image Analysis, with a particular emphasis on data-efficient learning, foundation models and explainable AI. Moreover, I am interested in Agentic Self-Improving AI, including continual learning and reinforcement learning for multi-agent systems.
I work on Deep Learning, Computer Vision, Medical Image Analysis, and
Self-Improving AI Systems. If you'd like to discuss ideas or explore a
collaboration, feel free to reach out via email or LinkedIn.
News
2026
Sep 01
Our team achieved Rank 1st at the BIC-MAC Challenge, MICCAI 2026
Jun 15
Our team achieved Rank 1st at the Multimedia Verification Challenge, ACM ICMR 2026
Jun 01
My paper ArgMAD was accepted to KES 2026
Apr 15
Our team achieved Rank 3rd at the WBCBench Challenge, IEEE ISBI 2026
Apr 01
My paper ACAL was accepted to Canadian AI 2026
Mar 01
My two papers were accepted as oral to IEEE ISBI 2026
Selected Publications
Robust White Blood Cell Classification with Stain-Normalized Decoupled Learning and Ensembling
IEEE 23rd International Symposium on Biomedical Imaging (ISBI) 2026
Geometry-Anchored PET-Aware Multimodal Pseudo-CT Synthesis for Whole-Body Attenuation Correction: The BIC-MAC Challenge
BIC-MAC Challenge, International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) 2026 1st Place
Argumentative Multi-Agent Debate for Explainable Depression Detection in Clinical Interviews
International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES) 2026