Fabrizio Assis
Johns Hopkins University, Johns Hopkins Bayview Medical Center
Papers
6
Total Citations
129
H-Index
5
About
Fabrizio Assis is pioneering a safer future for cardiac interventions by developing radiation-free image guidance technologies. His research centers on photoacoustic imaging and robotic visual servoing, aiming to replace fluoroscopy—which exposes patients and operators to ionizing radiation—during catheter-based procedures like radiofrequency ablation. Assis’s key contributions include the first *in vivo* demonstration of photoacoustic-guided cardiac catheter navigation with robotic visual servoing (76 citations), a foundational study that proved the concept’s clinical viability. To automate catheter tracking, he has advanced deep learning approaches for real-time catheter tip segmentation and localization in photoacoustic images, with multiple papers (19, 8, and 8 citations) refining these algorithms for *in vivo* settings. His work also addresses system reliability, introducing a beamformer-independent method to predict visual servoing failures from a single image frame. Collectively, Assis’s research integrates robotics, imaging physics, and machine learning to mitigate radiation risks while enhancing procedural precision—a compelling vision for the next generation of interventional cardiology.
Research Focus
Key Achievements
Top Papers
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