26 citations · 53 across the 14 of their papers we have counts for
7 papers · 1 filter
Semantic RGB--Depth Based Surgical Skill Assessment in Microscopic Stereo Videos
Jecia Z. Y. Mao, Sue M. Cho, Francis X. Creighton +3
Objective assessment of microsurgical technical skill is essential for competency-based training and quality assurance, yet existing video-based approaches predominantly rely on RG…
Speak, Segment, Track, Navigate: An Interactive System for Video-Guided Skull-Base Surgery
Jecia Z. Y. Mao, Francis X. Creighton, Russell H. Taylor +1
We introduce a speech-guided embodied agent framework for video-guided skull base surgery that dynamically executes perception and image-guidance tasks in response to surgeon queri…
SCOPE: Speech-guided COllaborative PErception Framework for Surgical Scene Segmentation
Jecia Z. Y. Mao, Francis X Creighton, Russell H Taylor +1
Accurate segmentation and tracking of relevant elements of the surgical scene is crucial to enable context-aware intraoperative assistance and decision making. Current solutions re…
TAToo: Vision-based Joint Tracking of Anatomy and Tool for Skull-base Surgery
Zhaoshuo Li, Hongchao Shu, Ruixing Liang +5
Purpose: Tracking the 3D motion of the surgical tool and the patient anatomy is a fundamental requirement for computer-assisted skull-base surgery. The estimated motion can be used…
Temporally Consistent Online Depth Estimation in Dynamic Scenes
Zhaoshuo Li, Wei Ye, Dilin Wang +4
Temporally consistent depth estimation is crucial for online applications such as augmented reality. While stereo depth estimation has received substantial attention as a promising…
On the Sins of Image Synthesis Loss for Self-supervised Depth Estimation
Zhaoshuo Li, Nathan Drenkow, Hao Ding +5
Scene depth estimation from stereo and monocular imagery is critical for extracting 3D information for downstream tasks such as scene understanding. Recently, learning-based method…
Revisiting Stereo Depth Estimation From a Sequence-to-Sequence Perspective with Transformers
Zhaoshuo Li, Xingtong Liu, Nathan Drenkow +4
Stereo depth estimation relies on optimal correspondence matching between pixels on epipolar lines in the left and right images to infer depth. In this work, we revisit the problem…