88 citations · 122 across the 8 of their papers we have counts for
9 papers
Intuitive Surgical SurgToolLoc and SurgVU Challenges Results: 2022-2025
Aneeq Zia, Max Berniker, Rogerio Garcia Nespolo +153
Robotic assisted (RA) surgery promises to transform surgical intervention. Intuitive Surgical is committed to fostering these changes and the machine learning models and algorithms…
Rethinking Causality-driven Robot Tool Segmentation with Temporal Constraints
Hao Ding, Jie Ying Wu, Zhaoshuo Li +1
Purpose: Vision-based robot tool segmentation plays a fundamental role in surgical robots and downstream tasks. CaRTS, based on a complementary causal model, has shown promising pe…
CaRTS: Causality-driven Robot Tool Segmentation from Vision and Kinematics Data
Hao Ding, Jintan Zhang, Peter Kazanzides +2
Vision-based segmentation of the robotic tool during robot-assisted surgery enables downstream applications, such as augmented reality feedback, while allowing for inaccuracies in…
An Interpretable Approach to Automated Severity Scoring in Pelvic Trauma
Anna Zapaishchykova, David Dreizin, Zhaoshuo Li +3
Pelvic ring disruptions result from blunt injury mechanisms and are often found in patients with multi-system trauma. To grade pelvic fracture severity in trauma victims based on w…
Estimation of Trocar and Tool Interaction Forces on the da Vinci Research Kit with Two-Step Deep Learning
Jie Ying Wu, Nural Yilmaz, Peter Kazanzides +1
Measurement of environment interaction forces during robotic minimally-invasive surgery would enable haptic feedback to the surgeon, thereby solving one long-standing limitation. E…
Relational Graph Learning on Visual and Kinematics Embeddings for Accurate Gesture Recognition in Robotic Surgery
Yonghao Long, Jie Ying Wu, Bo Lu +5
Automatic surgical gesture recognition is fundamentally important to enable intelligent cognitive assistance in robotic surgery. With recent advancement in robot-assisted minimally…
Multimodal and self-supervised representation learning for automatic gesture recognition in surgical robotics
Aniruddha Tamhane, Jie Ying Wu, Mathias Unberath
Self-supervised, multi-modal learning has been successful in holistic representation of complex scenarios. This can be useful to consolidate information from multiple modalities wh…
A County-level Dataset for Informing the United States' Response to COVID-19
Benjamin D. Killeen, Jie Ying Wu, Kinjal Shah +8
As the coronavirus disease 2019 (COVID-19) continues to be a global pandemic, policy makers have enacted and reversed non-pharmaceutical interventions with various levels of restri…
Leveraging Vision and Kinematics Data to Improve Realism of Biomechanic Soft-tissue Simulation for Robotic Surgery
Jie Ying Wu, Peter Kazanzides, Mathias Unberath
Purpose Surgical simulations play an increasingly important role in surgeon education and developing algorithms that enable robots to perform surgical subtasks. To model anatomy, F…