60 citations · 66 across the 3 of their papers we have counts for
4 papers · 1 filter
DUNEDepth: Bronchoscopic Depth and Pose Estimation via Hybrid Adaptation of a 3D-Vision Foundation Model
Qi Chang, Austin Kao, Ange Lou +1
State-of-the-art bronchoscopy guidance systems and computer-aided diagnosis methods have emerged as important tools for early lung cancer detection. Effective use of these tools de…
Autofluorescence Bronchoscopy Video Analysis for Lesion Frame Detection
Qi Chang, Rebecca Bascom, Jennifer Toth +2
Because of the significance of bronchial lesions as indicators of early lung cancer and squamous cell carcinoma, a critical need exists for early detection of bronchial lesions. Au…
Bronchoscopic video synchronization for interactive multimodal inspection of bronchial lesions
Qi Chang, Patrick D. Byrnes, Danish Ahmad +3
With lung cancer being the most fatal cancer worldwide, it is important to detect the disease early. A potentially effective way of detecting early cancer lesions developing along…
ESFPNet: efficient deep learning architecture for real-time lesion segmentation in autofluorescence bronchoscopic video
Qi Chang, Danish Ahmad, Jennifer Toth +2
Lung cancer tends to be detected at an advanced stage, resulting in a high patient mortality rate. Thus, much recent research has focused on early disease detection Bronchoscopy is…