5 papers
Automated Assessment of Kidney Ureteroscopy Exploration for Training
Fangjie Li, Nicholas Kavoussi, Charan Mohan +2
Purpose: Kidney ureteroscopic navigation is challenging with a steep learning curve. However, current clinical training has major deficiencies, as it requires one-on-one feedback f…
Monocular absolute depth estimation from endoscopy via domain-invariant feature learning and latent consistency
Hao Li, Daiwei Lu, Jesse d'Almeida +8
Monocular depth estimation (MDE) is a critical task to guide autonomous medical robots. However, obtaining absolute (metric) depth from an endoscopy camera in surgical scenes is di…
Focus on the Experts: Co-designing an Augmented Reality Eye-Gaze Tracking System with Surgical Trainees to Improve Endoscopic Instruction
Jumanh Atoum, Jinkyung Park, Mamtaj Akter +3
The current apprenticeship model for surgical training requires a high level of supervision, which does not scale well to meet the growing need for more surgeons. Many endoscopic p…
NAVIUS: Navigated Augmented Reality Visualization for Ureteroscopic Surgery
Ayberk Acar, Jumanh Atoum, Peter S. Connor +4
Ureteroscopy is the standard of care for diagnosing and treating kidney stones and tumors. However, current ureteroscopes have a limited field of view, requiring significant experi…
Augmented Reality-based Guidance with Deformable Registration in Head and Neck Tumor Resection
Qingyun Yang, Fangjie Li, Jiayi Xu +8
Head and neck squamous cell carcinoma (HNSCC) has one of the highest rates of recurrence cases among solid malignancies. Recurrence rates can be reduced by improving positive margi…