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Found 7 papers, 4 papers with code
Multi-scale and Cross-scale Contrastive Learning for Semantic Segmentation
We apply contrastive learning to enhance the discriminative power of the multi-scale features extracted by semantic segmentation networks.
Homography-based Visual Servoing with Remote Center of Motion for Semi-autonomous Robotic Endoscope Manipulation
Our approach allows a surgeon to build a graph of desired views, from which, once built, views can be manually selected and automatically servoed to irrespective of robot-patient frame transformation changes.
2020 CATARACTS Semantic Segmentation Challenge
In 2020, we released pixel-wise semantic annotations for anatomy and instruments for 4670 images sampled from 25 videos of the CATARACTS training set.
Deep Homography Estimation in Dynamic Surgical Scenes for Laparoscopic Camera Motion Extraction
We perform an extensive evaluation of state-of-the-art (SOTA) Deep Neural Networks (DNNs) across multiple compute regimes, finding our method transfers from our camera motion free da Vinci surgery dataset to videos of laparoscopic interventions, outperforming classical homography estimation approaches in both, precision by 41%, and runtime on a CPU by 43%.
Effective semantic segmentation in Cataract Surgery: What matters most?
Our work proposes neural network design choices that set the state-of-the-art on a challenging public benchmark on cataract surgery, CaDIS.
Ranked #1 on
2D Semantic Segmentation task 1 (8 classes)
on CaDIS
2D Semantic Segmentation task 1 (8 classes)
2D Semantic Segmentation task 2 (17 classes)
+2
Deep iterative vessel segmentation in OCT angiography
This paper addresses retinal vessel segmentation on optical coherence tomography angiography (OCT-A) images of the human retina.
Corner-Based Geometric Calibration of Multi-Focus Plenoptic Cameras
We propose a method for geometric calibration of multi-focus plenoptic cameras using raw images.
