David Owen
Papers
1
Total Citations
19
H-Index
1
About
David Owen is a researcher at the forefront of applying spatio-temporal deep learning to surgical video analysis. His most-cited work, "A spatio-temporal network for video semantic segmentation in surgical videos" (2023, 19 citations), introduces a novel architecture that captures both spatial and temporal dependencies in surgical footage, enabling precise, real-time segmentation of anatomical structures and instruments. This contribution addresses a critical challenge in computer-assisted surgery: the need for robust, context-aware models that can handle the dynamic, occluded environments of the operating room. Owen's approach leverages recurrent and convolutional components to maintain temporal coherence across frames, significantly improving segmentation accuracy over frame-by-frame methods. His work has direct implications for autonomous surgical guidance, skill assessment, and intraoperative decision support. With a growing citation impact, Owen is establishing himself as a key voice in the intersection of computer vision and minimally invasive surgery, pushing the boundaries of what AI can achieve in high-stakes medical settings.
Research Focus
Key Achievements
Top Papers
- 1A spatio-temporal network for video semantic segmentation in surgical videos19 citations · 2023