Naoto Kume
Papers
1
Total Citations
9
H-Index
1
About
Naoto Kume is a pioneering researcher in the intersection of robotic surgery and artificial intelligence, with a primary focus on enhancing haptic feedback in minimally invasive procedures. His most notable contribution is the development of a vision-based deep learning framework that estimates manipulation forces from laparoscopic surgical images, directly addressing the critical absence of tactile sensation in robot-assisted surgery. By making "pseudo-haptic feedback" explicit, Kume’s work enables surgeons to perceive forces visually, improving precision and safety during operations. His landmark 2024 study, conducted on porcine excised kidneys, has already garnered 9 citations, signaling its growing influence in surgical robotics. Kume’s research uniquely bridges computer vision, deep learning, and clinical practice, offering a non-invasive solution to a long-standing challenge in telesurgery. His findings not only advance the field of haptics but also pave the way for more intuitive human-machine interfaces in medicine. As a surgeon-researcher, Kume brings firsthand clinical insight to his work, ensuring that his innovations are both technically robust and directly applicable to real-world operating rooms.
Research Focus
Key Achievements
Top Papers
- 1