News

We have released the official code for our MICCAI 2025 paper on interactive segmentation of vascular structures.

Title: Multimodal Prompt Sequence Learning for Interactive Segmentation of Vascular Structures Authors: Jongsoo Lim, Soochahn Lee Code: github.com/kookmin-ee-ailab/mpsl-vessel-seg Paper: MICCAI 2025 proceedings

The released code covers training and inference for our prompt sequence model, which combines click- and text-based user interactions with SAM/CLIP encoders to enable accurate interactive segmentation of thin, branching vascular structures. We hope this will support the community in building on our work.

Our collaborative research with the University of Wisconsin-Madison on benchmarking multimodal LLMs has been accepted to CVPR Findings 2026.

Title: Contamination Detection for VLMs Using Multi‑Modal Semantic Perturbations Authors: Le Thien Phuc Nguyen, Zhuoran Yu, Samuel Low Yu Hang, Subin An, Jeongik Lee, Yohan Ban, SeungEun Chung, Thanh-Huy Nguyen, JuWan Maeng, Soochahn Lee, Yong Jae Lee

We look forward to presenting our work at ICLR 2026!

Soochahn Lee will be serving as an Area Chair for MICCAI 2026. In this role, he looks forward to evaluating the latest advancements in medical image computing and contributing to the success of the conference.

Our collaborative research with the University of Wisconsin-Madison has been accepted to ICLR 2026.

Title: Contamination Detection for VLMs Using Multi‑Modal Semantic Perturbations Authors: Jaden Park, Mu Cai, Feng Yao, Jingbo Shang, Soochahn Lee, Yong Jae Lee

We look forward to presenting our work at ICLR 2026!