Haoyun Wang
Papers
1
Total Citations
1
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About
Haoyun Wang is a rising researcher in the field of computer-assisted intervention and medical image analysis, with a primary focus on enhancing the precision and safety of vascular interventional surgery. His most notable contribution is the development of a lightweight attention network for guidewire segmentation and localization in clinical fluoroscopic images, a critical step in procedures like transcatheter arterial chemoembolization (TACE). This work addresses the fundamental challenge of accurately analyzing guidewire morphology to assist both robotic systems and physicians during surgery. By designing an efficient deep learning architecture that balances high segmentation accuracy with computational lightness, Wang’s approach is particularly suited for real-time clinical deployment. Although his most-cited paper is recent (2025), it has already garnered attention for its practical relevance in interventional radiology. Wang’s research sits at the intersection of computer vision, deep learning, and minimally invasive surgery, aiming to reduce procedural risks and improve patient outcomes. His work is especially valuable for researchers and engineers developing next-generation surgical robots and intraoperative guidance systems.
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