Congmin Yang
Papers
1
Total Citations
40
H-Index
1
About
Dr. Congmin Yang is a leading researcher in surgical vision and computer-assisted interventions, with a primary focus on advancing minimally invasive surgery through intelligent image analysis. Her most cited work, a comprehensive 2020 review on image-based laparoscopic tool detection and tracking using convolutional neural networks, has garnered 40 citations and serves as a foundational resource for the field. In this seminal paper, she systematically analyzed the challenges and state-of-the-art deep learning approaches for instrument localization without relying on cumbersome external tracking hardware, highlighting how surgical vision can overcome the limitations of traditional robotic encoders. Dr. Yang’s contributions have directly shaped the development of more accurate, real-time tool tracking systems that are critical for computer- and robotic-assisted surgery, improving intraoperative guidance and safety. Her research bridges computer vision and clinical practice, offering practical solutions that reduce the need for additional sensors while enhancing surgical precision. Through her work, Dr. Yang has established herself as a key voice in the integration of AI into the operating room, inspiring further innovations in autonomous surgical assistance and intraoperative decision support.
Research Focus
Key Achievements
Top Papers
- 1