Damjan Vukovic

Papers

Total Citations

H-Index

About

Damjan Vukovic is a leading researcher at the intersection of deep learning, medical imaging, and autonomous robotic surgery, with a primary focus on advancing minimally invasive orthopaedic procedures. His most impactful work centers on developing intelligent systems for real-time ultrasound (US) image quality assessment and autonomous knee arthroscopy, where he has pioneered the use of deep convolutional neural networks to detect femoral cartilage boundaries with high precision. This contribution is critical for enabling safe, real-time volumetric US guidance in robotic surgery, addressing the risk of unintended cartilage injury and postoperative complications. His 2020 paper on this topic has garnered 15 citations, reflecting its influence in the emerging field of autonomous surgical navigation. Beyond this, Vukovic’s research spans the broader application of computer vision and machine learning to surgical robotics, where his work on boundary detection and image quality assessment has laid foundational groundwork for safer, more autonomous arthroscopic procedures. His achievements are notable for bridging the gap between deep learning and clinical robotics, offering a pathway to reduce human error in complex surgeries.