Search Results for author:
Found 6 papers, 3 papers with code
Learning How To Robustly Estimate Camera Pose in Endoscopic Videos
Purpose: Surgical scene understanding plays a critical role in the technology stack of tomorrow's intervention-assisting systems in endoscopic surgeries.
Fused Detection of Retinal Biomarkers in OCT Volumes
In this context, we present a method that automatically predicts the presence of biomarkers in OCT cross-sections by incorporating information from the entire volume.
Deep Multi Label Classification in Affine Subspaces
We evaluate the method using two MLC medical imaging datasets and show a large performance increase compared to previous multi-label frameworks.
2017 Robotic Instrument Segmentation Challenge
In mainstream computer vision and machine learning, public datasets such as ImageNet, COCO and KITTI have helped drive enormous improvements by enabling researchers to understand the strengths and limitations of different algorithms via performance comparison.
Comparative evaluation of instrument segmentation and tracking methods in minimally invasive surgery
The paper presents a comparative validation study of different vision-based methods for instrument segmentation and tracking in the context of robotic as well as conventional laparoscopic surgery.
Simultaneous Recognition and Pose Estimation of Instruments in Minimally Invasive Surgery
An additional advantage of our approach is that instrument detection at test time is achieved while avoiding the need for scale-dependent sliding window evaluation.
