Semantic RGB--Depth Based Surgical Skill Assessment in Microscopic Stereo Videos
Objective assessment of microsurgical technical skill is essential for competency-based training and quality assurance, yet existing video-based approaches predominantly rely on RGB images and therefore overlook the 3D spatial relationships that characterize instrument-anatomy interactions. Although stereo operating microscopes provide complementary depth information, conventional stereo matching algorithms can produce sparse and unreliable depth estimates under high-magnification imaging conditions, limiting their use for automated skill assessment. This work presents a semantic RGB-Depth framework for surgical skill assessment from microscopic stereo videos. A regression-based depth fus...
| Authors | Jecia Z. Y. Mao, Sue M. Cho, Francis X. Creighton et al. |
|---|---|
| Primary category | cs.CV |
| Published | 1 October 2026 |
| Last updated at source | 1 October 2026 |
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