6 papers
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…