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Found 5 papers, 3 papers with code
Autonomous Catheterization with Open-source Simulator and Expert Trajectory
Endovascular robots have been actively developed in both academia and industry.
Shape-Sensitive Loss for Catheter and Guidewire Segmentation
By computing the cosine similarity between these feature vectors, we gain a nuanced understanding of image similarity that goes beyond the limitations of traditional overlap-based measures.
Language Semantic Graph Guided Data-Efficient Learning
Therefore, to achieve data-efficient learning, researchers typically explore approaches that can leverage more related or unlabeled data without necessitating additional manual labeling efforts, such as Semi-Supervised Learning (SSL), Transfer Learning (TL), and Data Augmentation (DA).
Translating Simulation Images to X-ray Images via Multi-Scale Semantic Matching
In this paper, we propose a new method to translate simulation images from an endovascular simulator to X-ray images.
Borrowing Knowledge From Pre-trained Language Model: A New Data-efficient Visual Learning Paradigm
To address this issue, this paper presents a novel approach that seeks to leverage linguistic knowledge for data-efficient visual learning.
