Ko Ko Zayar Toe
Papers
1
Total Citations
12
H-Index
1
About
Ko Ko Zayar Toe is a rising researcher in the field of computer-assisted surgery, with a primary focus on medical image analysis and deep learning for laparoscopic and robotic interventions. His most impactful contribution to date is the creation of **CholecInstanceSeg**, a novel dataset and benchmark for tool instance segmentation in laparoscopic surgery, published in 2025. This work addresses a critical gap in the field by providing comprehensive pixel-level annotations for surgical tools, enabling the development of more precise and reliable computer vision models for real-time surgical assistance. Already garnering **12 citations** shortly after its release, CholecInstanceSeg has quickly become a foundational resource for researchers working on surgical scene understanding and autonomous robotic systems. By tackling the challenge of tool segmentation in complex, dynamic surgical environments, Toe’s work directly supports advances in intraoperative decision support, surgical skill assessment, and patient safety. His research promises to accelerate the integration of AI into the operating room, making minimally invasive procedures safer and more efficient.
Research Focus
Key Achievements
Top Papers
- 1