Suphachoke Sonsilphong
Papers
3
Total Citations
23
H-Index
2
About
Suphachoke Sonsilphong is a researcher advancing the frontiers of robotic-assisted laparoscopic surgery through deep learning and computer vision. His primary research areas include surgical instrument detection, laparoscope manipulation, and autonomous robotic navigation in minimally invasive procedures. Sonsilphong’s major contribution lies in developing deep learning-based object detection systems that enable real-time identification and tracking of surgical instruments during laparoscopic operations. His most cited work, “Surgical Instrument Detection for Laparoscopic Surgery using Deep Learning” (2022, 18 citations), demonstrates a robust framework for enhancing the precision and safety of robot-assisted surgery by preventing instrument collisions and tissue damage. He further extended this approach in his studies on the Laparoscope Manipulating Robot (LMR), where his detection system supports autonomous camera control, reducing the cognitive load on surgeons. With cumulative citations reflecting growing interest in his work, Sonsilphong’s innovations are pivotal for the next generation of intelligent surgical robotics, offering tangible improvements in operative efficiency and patient outcomes. His research stands at the intersection of AI and healthcare, promising safer, more effective minimally invasive procedures.
Research Focus
Key Achievements
Top Papers
- 1Surgical Instrument Detection for Laparoscopic Surgery using Deep Learning18 citations · 2022
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