no code implementations • 11 Mar 2024 • Jiaxin Guo, Jiangliu Wang, Zhaoshuo Li, Tongyu Jia, Qi Dou, Yun-hui Liu
Soft tissue tracking is crucial for computer-assisted interventions.
1 code implementation • CVPR 2023 • Zhaoshuo Li, Thomas Müller, Alex Evans, Russell H. Taylor, Mathias Unberath, Ming-Yu Liu, Chen-Hsuan Lin
Neural surface reconstruction has been shown to be powerful for recovering dense 3D surfaces via image-based neural rendering.
1 code implementation • 29 Dec 2022 • Zhaoshuo Li, Hongchao Shu, Ruixing Liang, Anna Goodridge, Manish Sahu, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
TAToo jointly tracks the rigid 3D motion of patient skull and surgical drill from stereo microscopic videos.
1 code implementation • 30 Nov 2022 • Hao Ding, Jie Ying Wu, Zhaoshuo Li, Mathias Unberath
Method: To address the above limitations, we take temporal relation into consideration and propose a temporal causal model for robot tool segmentation on video sequences.
1 code implementation • 21 Nov 2022 • Hongchao Shu, Ruixing Liang, Zhaoshuo Li, Anna Goodridge, Xiangyu Zhang, Hao Ding, Nimesh Nagururu, Manish Sahu, Francis X. Creighton, Russell H. Taylor, Adnan Munawar, Mathias Unberath
Twin-S tracks and updates the virtual model in real-time given measurements from modern tracking technologies.
1 code implementation • 21 Oct 2022 • Weiyu Guo, Zhaoshuo Li, Yongkui Yang, Zheng Wang, Russell H. Taylor, Mathias Unberath, Alan Yuille, Yingwei Li
We construct our stereo depth estimation model, Context Enhanced Stereo Transformer (CSTR), by plugging CEP into the state-of-the-art stereo depth estimation method Stereo Transformer.
1 code implementation • 19 Feb 2022 • Xingtong Liu, Zhaoshuo Li, Masaru Ishii, Gregory D. Hager, Russell H. Taylor, Mathias Unberath
In endoscopy, many applications (e. g., surgical navigation) would benefit from a real-time method that can simultaneously track the endoscope and reconstruct the dense 3D geometry of the observed anatomy from a monocular endoscopic video.
no code implementations • 17 Nov 2021 • Zhaoshuo Li, Wei Ye, Dilin Wang, Francis X. Creighton, Russell H. Taylor, Ganesh Venkatesh, Mathias Unberath
We present a framework named Consistent Online Dynamic Depth (CODD) to produce temporally consistent depth estimates in dynamic scenes in an online setting.
no code implementations • 13 Sep 2021 • Zhaoshuo Li, Nathan Drenkow, Hao Ding, Andy S. Ding, Alexander Lu, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
It is based on the idea that observed frames can be synthesized from neighboring frames if accurate depth of the scene is known - or in this case, estimated.
2 code implementations • 1 Jul 2021 • Yonghao Long, Zhaoshuo Li, Chi Hang Yee, Chi Fai Ng, Russell H. Taylor, Mathias Unberath, Qi Dou
After that, a dynamic reconstruction algorithm which can estimate the tissue deformation and camera movement, and aggregate the information over time is proposed for surgical scene reconstruction.
no code implementations • 21 May 2021 • Anna Zapaishchykova, David Dreizin, Zhaoshuo Li, Jie Ying Wu, Shahrooz Faghih Roohi, Mathias Unberath
The method operates similarly to human interpretation of CT scans and first detects distinct pelvic fractures on CT with high specificity using a Faster-RCNN model that are then interpreted using a structural causal model based on clinical best practices to infer an initial Tile grade.
1 code implementation • ICCV 2021 • Zhaoshuo Li, Xingtong Liu, Nathan Drenkow, Andy Ding, Francis X. Creighton, Russell H. Taylor, Mathias Unberath
Stereo depth estimation relies on optimal correspondence matching between pixels on epipolar lines in the left and right images to infer depth.
1 code implementation • 3 Jun 2020 • Zhaoshuo Li, Alex Gordon, Thomas Looi, James Drake, Christopher Forrest, Russell H. Taylor
This paper presents a dynamic constraint formulation to provide protective virtual fixtures of 3D anatomical structures from polygon mesh representations.
Robotics Systems and Control Systems and Control
no code implementations • 20 Mar 2020 • Zhaoshuo Li, Amirreza Shaban, Jean-Gabriel Simard, Dinesh Rabindran, Simon DiMaio, Omid Mohareri
Purpose: We describe a 3D multi-view perception system for the da Vinci surgical system to enable Operating room (OR) scene understanding and context awareness.