Mazda Farshad
Papers
9
Total Citations
87
H-Index
6
About
Mazda Farshad is a pioneering researcher in orthopaedic surgery, with a focus on advancing spinal fusion techniques through robotics, augmented reality (AR), and artificial intelligence. His major contributions lie in developing non-radiative, robot-assisted ultrasound navigation systems for pedicle screw placement, which enhance accuracy while reducing radiation exposure. Farshad’s work on SafeRPlan, a deep reinforcement learning framework for intraoperative planning, addresses critical safety challenges in spinal surgery by optimizing screw trajectories near vital structures. He has also explored domain adaptation for 3D lumbar spine reconstruction from fluoroscopy, aiming to overcome barriers like cost and workflow integration in surgical navigation. His comparative study of AR versus robotic-assisted surgery for pedicle screw placement (9 citations) provides valuable clinical insights. Additionally, Farshad’s custom-built rod bending machine reduces residual forces in spinal fusion, improving implant outcomes. With papers accumulating over 80 citations, including his highly cited robot-assisted ultrasound study (26 citations), Farshad’s work is shaping the future of orthopaedic surgery by merging robotics, imaging, and machine learning to enhance precision and patient safety.
Research Focus
Key Achievements
Top Papers
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- 7Robotics in orthopaedic surgery: The end of surgery or its future?6 citations · 2024
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- 9Safe Deep RL for Intraoperative Planning of Pedicle Screw Placement2 citations · 2023