12 accepted papers
Low-Rank Adaptation (LoRA) has proven effective in reducing computational costs while maintaining performance comparable to fully fine-tuned foundation models across various tasks. However, its fixed low-rank structure restricts its adaptability in scenarios with substantial domain gaps, where highe…
Robot assisted endoluminal intervention is an emerging tool for treating luminal lesions. Vision-based endoluminal navigation, particularly through video-CT registration, is a tangible way of obtaining absolute camera position information. By using pre-operative CT data, accurate endoscope localizat
Robot assisted endoluminal intervention is an emerging technique for both benign and malignant luminal lesions. With vision-based navigation, when combined with pre-operative imaging data as priors, it is possible to recover position and pose of the endoscope without the need of additional sensors.
Webly supervised learning has attracted increasing attention for its effectiveness in exploring publicly accessible data at scale without manual annotation. However, most existing methods of learning with web datasets are faced with challenges from label noise, and they have limited assumptions on c…
Endobronchial intervention is increasingly used as a minimally invasive means for the treatment of pulmonary diseases. In order to reduce the difficulty of manipulation in complex airway networks, robust lumen detection is essential for intraoperative guidance. However, these methods are sensitive t…
Recently, webly supervised learning (WSL) has been studied to leverage numerous and accessible data from the Internet. Most existing methods focus on learning noise-robust models from web images while neglecting the performance drop caused by the differences between web domain and real-world domain.…
Semantic segmentation of surgical instruments provides essential priors for autonomous surgery. This task is however challenging since the fine-structure of surgical instruments requires the accurate segmentation of detailed regions in images. As the visual guidance for autonomous surgery, the algor…
Optical microscopy imaging is the gold standard for the diagnosis of cancers since it allows the cell-level visualization of tissues. The high quality of imaging is largely determined by the focus distances between the lens and objects. Therefore, a robust and efficient auto focusing algorithm is re
Segmentation of skin lesions is important for disease diagnoses and treatment planning. Over the years, semi-supervised methods using pseudo labels have boosted the segmentation performance with limited labeled data and abundant unlabeled data. However, the unreliable targets in pseudo labels might…
Endobronchial intervention is increasingly used as a minimally invasive means of lung intervention. Vision-based localization approaches are often sensitive to image artifacts in bronchoscopic videos. In this letter, a robust navigation system based on a context-aware depth recovery approach for mon
Task autonomy is an important consideration for the development of future surgical robots. For robot-assisted anastomosis, suture thread detection is a prerequisite for subsequent robot manipulation. Previous works on automatic thread detection are focused on the learning of the models with specific…
The technique of robust suture detection is vital in many applications including trainee suturing skill evaluation, suture augmentation in robotic-assisted surgery and suture recognition for automatic suturing. Due to the complicated environment of surgery, the detection of a suture is challenged by…