Papers
2
Total Citations
36
H-Index
2
About
Karim Botros is an emerging researcher at the forefront of medical microrobotics and biomedical imaging, with a particular focus on leveraging deep learning to advance the detection and tracking of microscale robotic systems. His work addresses one of the most pressing challenges in translational microrobotics: enabling fully automatic, real-time localization of microrobots within the human body using clinically accessible imaging modalities such as ultrasound. Botros's most notable contributions include the development of deep learning-based frameworks capable of detecting and tracking chain-like magnetic microsphere robots autonomously, removing the need for manual intervention and bringing these systems closer to clinical applicability. His research extends to benchmarking efforts, exemplified by the USMicroMagSet dataset, which provides standardized tools for evaluating microrobot performance in ultrasound imagery — a foundational resource for the broader research community. With each of his key publications accumulating 18 citations, Botros's work is gaining meaningful traction in a highly specialized and rapidly evolving field. His research sits at a compelling intersection of robotics, medical imaging, and artificial intelligence, positioning him as a promising contributor to the future of minimally invasive surgery and targeted drug delivery systems.
Research Focus
Key Achievements
Top Papers
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