Yordanka Velikova

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About

Yordanka Velikova is a rising researcher at the intersection of medical imaging, robotics, and artificial intelligence, with a primary focus on advancing ultrasound (US) technology for clinical diagnosis. Her work centers on overcoming critical limitations of US imaging—namely operator variability, shadowing artifacts, and lack of 3D context—by integrating implicit neural representations and robotic systems. In her 2024 paper on breathing-compensated volume reconstruction in robotic ultrasound (11 citations), she pioneered a method to mitigate respiratory motion artifacts, a key barrier to reliable abdominal screening. Her development of CACTUSS (Common Anatomical CT-US Space, 9 citations) provides a framework for aligning CT and US modalities, directly targeting the detection of abdominal aortic aneurysms. More recently, she has tackled spinal imaging, using shape completion and real-time visualization to compensate for acoustic shadowing during robotic acquisitions. While still early in her career, Velikova’s work has already garnered attention for its practical, translational impact—bridging the gap between raw US data and actionable anatomical insights. Her contributions promise to make ultrasound a more robust, reproducible tool for screening and image-guided interventions.