The paper is accepted for presentation at IPCAI2025, and weโre especially humbled to receive the ๐น๐๐จ ๐ฆ๐๐ฟ๐ฎ๐๐ฏ๐ผ๐๐ฟ๐ด ๐ฎ๐ป๐ฑ ๐ก๐๐น ๐๐ฒ๐ป๐ฐ๐ต ๐๐ผ ๐๐ฒ๐ฑ๐๐ถ๐ฑ๐ฒ ๐๐๐ฎ๐ฟ๐ฑ: ๐๐ผ๐ป๐ผ๐ฟ๐ฎ๐ฏ๐น๐ฒ ๐ ๐ฒ๐ป๐๐ถ๐ผ๐ป.
In this work, we address the challenge of accurately delineating the dissection zones during endoscopic submucosal dissection procedures. By integrating flexible visual cuesโsuch as scribbles and bounding boxesโdirectly onto surgical images, our PDZSeg model guides segmentation for both better precision and enhanced safety. Leveraging a state-of-the-art foundation model (DINOv2) and an efficient LoRA training strategy, we fine-tuned our approach on the specialized ESD-DZSeg dataset. Our experimental results show promising improvements over traditional methods, offering robust support for intraoperative guidance and remote surgical training.
Our sincere thanks to every colleague (Mengya Xu, Wenjin Mo, Guankun Wang, Huxin Gao, An Wang), mentor (Dr. Ning Zhong, Dr. Zhen Li, Dr. Xiaoxiao Yang, Prof. Hongliang Ren), and community member whose support has been indispensable. This achievement reaffirms our collective effort and inspires us to further refine robotic-assisted techniques towards enhanced safety and effectiveness.
Paper available at: https://lnkd.in/g7KcytnE
