activity
20232026
most citedAdvancing Depth Anything Model for Unsupervised Monocular Depth Estimation in Endoscopy

1 citations · 1 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Hierarchical Prototype-Memory Adaptation of SAM for Surgical Instrument Segmentation

Xinning Yao, Jingjing Wang, Jinghua Yue +3

Surgical instrument segmentation (SIS) is fundamental for computer-assisted surgery, where reliable instrument masks enable precise scene understanding and clinical assistance. Rec…

cs.CV2025

EndoUFM: Utilizing Foundation Models for Monocular depth estimation of endoscopic images

Xinning Yao, Bo Liu, Bojian Li +3

Depth estimation is a foundational component for 3D reconstruction in minimally invasive endoscopic surgeries. However, existing monocular depth estimation techniques often exhibit…

eess.IV2025

Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge

Muhammad Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman +60

Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aort…

cs.CV2024★ 1 cited

Advancing Depth Anything Model for Unsupervised Monocular Depth Estimation in Endoscopy

Bojian Li, Bo Liu, Xinning Yao +2

Depth estimation is a cornerstone of 3D reconstruction and plays a vital role in minimally invasive endoscopic surgeries. However, most current depth estimation networks rely on tr…

eess.IV2023

RT-SRTS: Angle-Agnostic Real-Time Simultaneous 3D Reconstruction and Tumor Segmentation from Single X-Ray Projection

Miao Zhu, Qiming Fu, Bo Liu +4

Radiotherapy is one of the primary treatment methods for tumors, but the organ movement caused by respiration limits its accuracy. Recently, 3D imaging from a single X-ray projecti…