Raphaela Maerkl
Papers
1
Total Citations
2
H-Index
1
About
Raphaela Maerkl is a leading researcher at the intersection of computer vision and surgical data science, with a primary focus on advancing automated analysis of endoscopic procedures. Her work centers on developing and validating machine learning models for surgical phase recognition, instrument keypoint estimation, and instrument instance segmentation—critical components for building intelligent surgical assistance systems. Maerkl’s most notable contribution is her leadership in the PhaKIR 2024 challenge, a landmark comparative validation study that established standardized benchmarks for these three core tasks in endoscopy. This work, published in 2026, provides the surgical AI community with rigorous evaluation frameworks and baseline results, directly enabling more reproducible and clinically translatable research. While her publication record is early-stage, with the PhaKIR paper already garnering citations, her methodological rigor in designing multi-task challenges positions her as an emerging authority in surgical scene understanding. Maerkl’s research is pivotal for future autonomous surgical systems, offering foundational tools that promise to improve intraoperative decision support and surgical training through precise, real-time analysis of endoscopic video.
Research Focus
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Top Papers
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