Henrique Alexandrino
Papers
3
Total Citations
248
H-Index
3
About
Henrique Alexandrino is a leading researcher at the intersection of computer vision, robotics, and medical imaging, with a primary focus on advancing endoscopic Simultaneous Localization and Mapping (SLAM) technologies. His most impactful contribution is the creation of the **EndoSLAM dataset**, a comprehensive benchmark that addresses a critical gap in the field by enabling quantitative evaluation of SLAM methods for minimally invasive surgery. This foundational work, detailed in his highly cited 2021 paper (240 citations), provides the research community with a standardized platform to assess dense topography reconstruction and pose estimation. Alexandrino’s innovative approach also includes the development of **Endo-SfMLearner**, an unsupervised monocular visual odometry and depth estimation framework that leverages deep learning to overcome the challenges of endoscopic video analysis. By combining a rigorous dataset with novel algorithmic solutions, his research directly enhances the accuracy and reliability of surgical navigation systems. His work is essential reading for anyone developing autonomous or assistive tools for endoscopy, establishing him as a key figure in the push toward more intelligent, data-driven surgical robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2
- 3Quantitative Evaluation of Endoscopic SLAM Methods: EndoSLAM Dataset.3 citations · 2020