Papers
1
Total Citations
7
H-Index
1
About
Mingwei Wen is a rising researcher at the intersection of computer vision, medical robotics, and deep learning, with a primary focus on advancing force sensing and perception in minimally invasive procedures. His most notable work, "TransVFS: A spatio-temporal local–global transformer for vision-based force sensing during ultrasound-guided prostate biopsy" (2024), introduces a novel transformer architecture that captures both local and global spatio-temporal features from video data to estimate tool-tissue interaction forces without physical sensors. This contribution is pivotal for improving safety and accuracy in robotic-assisted biopsies, offering a non-invasive, real-time sensing solution. Although early in his career, Wen’s work has already garnered 7 citations, signaling growing interest from the surgical robotics and medical imaging communities. His research bridges the gap between high-level visual understanding and low-level physical sensing, with potential applications in autonomous surgery and haptic feedback systems. Wen’s innovative use of transformers for force estimation marks a significant step toward more intelligent, context-aware surgical tools, positioning him as a promising contributor to next-generation medical technologies.
Research Focus
Key Achievements
Top Papers
- 1