Susanne Feldhaus
Papers
1
Total Citations
2
H-Index
1
About
Susanne Feldhaus is a researcher at the forefront of advancing surgical navigation through cutting-edge computer vision and optical imaging. Her primary research focuses on developing markerless motion detection techniques for robot-assisted and minimally invasive surgery, leveraging volumetric optical coherence tomography (OCT) data. Her most notable contribution, the 2021 paper "In-vivo markerless motion detection from volumetric optical coherence tomography data using CNNs," addresses a critical challenge in the field: the reliance on optical markers and the scarcity of distinct anatomical features on skin or organs that complicate tissue tracking with commercial systems. By demonstrating the feasibility of using convolutional neural networks (CNNs) to detect motion directly from 3D OCT data without external markers, Feldhaus has opened new pathways for more precise and autonomous surgical navigation. This work, which has garnered 2 citations, underscores her impact in bridging deep learning with biomedical optics. Her achievements highlight a commitment to solving real-world surgical problems, making her a promising voice in the intersection of medical imaging and robotics.
Research Focus
Key Achievements
Top Papers
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