26 citations · 53 across the 14 of their papers we have counts for
16 papers
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…
Autonomous Robotic System with Optical Coherence Tomography Guidance for Vascular Anastomosis
Jesse Haworth, Rishi Biswas, Justin Opfermann +7
Vascular anastomosis, the surgical connection of blood vessels, is essential in procedures such as organ transplants and reconstructive surgeries. The precision required limits acc…
Beyond the Manual Touch: Situational-aware Force Control for Increased Safety in Robot-assisted Skullbase Surgery
Hisashi Ishida, Deepa Galaiya, Nimesh Nagururu +4
Purpose - Skullbase surgery demands exceptional precision when removing bone in the lateral skull base. Robotic assistance can alleviate the effect of human sensory-motor limitatio…
Integrating 3D Slicer with a Dynamic Simulator for Situational Aware Robotic Interventions
Manish Sahu, Hisashi Ishida, Laura Connolly +6
Image-guided robotic interventions represent a transformative frontier in surgery, blending advanced imaging and robotics for improved precision and outcomes. This paper addresses…
Haptic-Assisted Collaborative Robot Framework for Improved Situational Awareness in Skull Base Surgery
Hisashi Ishida, Manish Sahu, Adnan Munawar +5
Skull base surgery is a demanding field in which surgeons operate in and around the skull while avoiding critical anatomical structures including nerves and vasculature. While imag…
A force-sensing surgical drill for real-time force feedback in robotic mastoidectomy
Yuxin Chen, Anna Goodridge, Manish Sahu +7
Purpose: Robotic assistance in otologic surgery can reduce the task load of operating surgeons during the removal of bone around the critical structures in the lateral skull base.…
Improving Surgical Situational Awareness with Signed Distance Field: A Pilot Study in Virtual Reality
Hisashi Ishida, Juan Antonio Barragan, Adnan Munawar +6
The introduction of image-guided surgical navigation (IGSN) has greatly benefited technically demanding surgical procedures by providing real-time support and guidance to the surge…
Fully Immersive Virtual Reality for Skull-base Surgery: Surgical Training and Beyond
Adnan Munawar, Zhaoshuo Li, Nimesh Nagururu +4
Purpose: A virtual reality (VR) system, where surgeons can practice procedures on virtual anatomies, is a scalable and cost-effective alternative to cadaveric training. The fully d…
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…
Twin-S: A Digital Twin for Skull-base Surgery
Hongchao Shu, Ruixing Liang, Zhaoshuo Li +9
Purpose: Digital twins are virtual interactive models of the real world, exhibiting identical behavior and properties. In surgical applications, computational analysis from digital…
Virtual Reality for Synergistic Surgical Training and Data Generation
Adnan Munawar, Zhaoshuo Li, Punit Kunjam +7
Surgical simulators not only allow planning and training of complex procedures, but also offer the ability to generate structured data for algorithm development, which may be appli…
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…