5 citations · 8 across the 11 of their papers we have counts for
11 papers
Geometry-Aware Camera Localization for Bronchoscopy
Lumin Chen, Qingyao Tian, Jinpeng Li +5
Camera localization in bronchoscopy remains a challenging problem due to stringent accuracy requirements, real-time constraints, and limited training data. Compared to natural scen…
BREATH-VL: Vision-Language-Guided 6-DoF Bronchoscopy Localization via Semantic-Geometric Fusion
Qingyao Tian, Bingyu Yang, Huai Liao +4
Vision-language models (VLMs) have recently shown remarkable performance in navigation and localization tasks by leveraging large-scale pretraining for semantic understanding. Howe…
EndoMatcher: Generalizable Endoscopic Image Matcher via Multi-Domain Pre-training for Robot-Assisted Surgery
Bingyu Yang, Qingyao Tian, Yimeng Geng +4
Generalizable dense feature matching in endoscopic images is crucial for robot-assisted tasks, including 3D reconstruction, navigation, and surgical scene understanding. Yet, it re…
Harnessing Foundation Models for Robust and Generalizable 6-DOF Bronchoscopy Localization
Qingyao Tian, Huai Liao, Xinyan Huang +2
Vision-based 6-DOF bronchoscopy localization offers a promising solution for accurate and cost-effective interventional guidance. However, existing methods struggle with 1) limited…
EndoMamba: An Efficient Foundation Model for Endoscopic Videos via Hierarchical Pre-training
Qingyao Tian, Huai Liao, Xinyan Huang +4
Endoscopic video-based tasks, such as visual navigation and surgical phase recognition, play a crucial role in minimally invasive surgeries by providing real-time assistance. While…
Enhancing Bronchoscopy Depth Estimation through Synthetic-to-Real Domain Adaptation
Qingyao Tian, Huai Liao, Xinyan Huang +2
Monocular depth estimation has shown promise in general imaging tasks, aiding in localization and 3D reconstruction. While effective in various domains, its application to bronchos…
Progressive Curriculum Learning with Scale-Enhanced U-Net for Continuous Airway Segmentation
Bingyu Yang, Qingyao Tian, Huai Liao +4
Continuous and accurate segmentation of airways in chest CT images is essential for preoperative planning and real-time bronchoscopy navigation. Despite advances in deep learning f…
EndoOmni: Zero-Shot Cross-Dataset Depth Estimation in Endoscopy by Robust Self-Learning from Noisy Labels
Qingyao Tian, Zhen Chen, Huai Liao +4
Single-image depth estimation is essential for endoscopy tasks such as localization, reconstruction, and augmented reality. Most existing methods in surgical scenes focus on in-dom…
PANS: Probabilistic Airway Navigation System for Real-time Robust Bronchoscope Localization
Qingyao Tian, Zhen Chen, Huai Liao +4
Accurate bronchoscope localization is essential for pulmonary interventions, by providing six degrees of freedom (DOF) in airway navigation. However, the robustness of current visi…
DD-VNB: A Depth-based Dual-Loop Framework for Real-time Visually Navigated Bronchoscopy
Qingyao Tian, Huai Liao, Xinyan Huang +5
Real-time 6 DOF localization of bronchoscopes is crucial for enhancing intervention quality. However, current vision-based technologies struggle to balance between generalization t…
BronchoTrack: Airway Lumen Tracking for Branch-Level Bronchoscopic Localization
Qingyao Tian, Huai Liao, Xinyan Huang +5
Localizing the bronchoscope in real time is essential for ensuring intervention quality. However, most existing methods struggle to balance between speed and generalization. To add…