Papers
5
Total Citations
69
H-Index
4
About
Lidia Al-Zogbi is a pioneering researcher at the intersection of medical robotics, computer vision, and autonomous surgical systems. Her work focuses on developing intelligent robotic platforms for minimally invasive interventions, with key contributions spanning autonomous ultrasound imaging, needle steering, and 3D scene reconstruction for surgery. During the COVID-19 pandemic, she led the development of an autonomous robotic Point-of-Care Ultrasound system for monitoring pulmonary diseases, a highly cited work (26 citations) that addressed a critical clinical need. Her research on deep learning-based skin segmentation for novel abdominal datasets (24 citations) expanded the application of computer vision beyond traditional facial and hand datasets. Al-Zogbi has also made significant advances in modeling bevel-tip needle deflection in multi-layer tissues (12 citations), improving the accuracy of percutaneous interventions. Notably, she co-developed SlicerROS2, an open-source software module integrating 3D Slicer with the Robot Operating System, providing a standardized platform for image-guided robotic interventions research. Her most recent work explores monocular vision for autonomous tumor resection guidance, demonstrating her commitment to translating computer vision into actionable surgical robotics. With over 69 total citations, Al-Zogbi’s research is shaping the future of autonomous, image-guided medical interventions.
Research Focus
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Top Papers
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