Alejandro Martin‐Gomez
Papers
10
Total Citations
78
H-Index
5
About
Alejandro Martin-Gomez is a leading researcher at the intersection of medical robotics, mixed reality, and ophthalmic surgery. His work focuses on developing intelligent systems that enhance surgical precision and autonomy, particularly for delicate procedures like subretinal injection—a treatment for vitreoretinal disorders. Martin-Gomez’s major contributions include pioneering robotic navigation autonomy for subretinal injection using real-time virtual intraoperative Optical Coherence Tomography (iOCT) volume slicing, a method that leverages convolutional neural networks for rapid instrument pose estimation. His deep learning-based registration approach for OCT-guided robotic injections has further advanced this field, with his top-cited paper accumulating 27 citations. Beyond ophthalmic applications, he has made significant strides in mixed reality interfaces for robotic X-ray systems and uncertainty-aware shape estimation of surgical continuum manipulators using Fiber Bragg Grating sensors. His work on extending the Segment Anything Model for medical imaging has garnered attention in the medical AI community. Martin-Gomez’s research, consistently published in top venues, demonstrates a unique ability to bridge virtual and real environments, enabling safer, more accurate robotic-assisted interventions. His achievements position him as a key innovator in next-generation surgical robotics.
Research Focus
Key Achievements
Top Papers
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- 3Segment any medical model extended11 citations · 2024
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