4 citations · 5 across the 9 of their papers we have counts for
12 papers
Object-Centered Reconstruction for Vision-Based 3D Force Estimation
Zhonghao Zhang, Mingyeung Wu, Hao Yang +3
Excessive force may damage tissue and increase the risk of anastomotic leakage in robotic colorectal surgery. Although the da Vinci 5 provides force sensing, this capability is una…
Differentiable Mesh State Estimation via Factor Graph Inference for Deformable Object Reconstruction
Lidia Al-Zogbi, Fangjie Li, Samuel Tobin +13
Estimating deformable object states remains a fundamental challenge in robotics and simulation. We propose a novel factor graph-based framework for probabilistic mesh state estimat…
Contour-Constrained Deformable Registration with Parameter Characterization for Head and Neck Surgical Guidance
Qingyun Yang, Jon S. Heiselman, Ayberk Acar +5
With 890,000 annual new cases globally, head and neck squamous cell carcinoma has one of the highest recurrence rates among solid malignancies. Although frozen section analysis is…
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
A Supervised Autonomous Resection and Retraction Framework for Transurethral Enucleation of the Prostatic Median Lobe
Mariana Smith, Tanner Watts, Susheela Sharma Stern +15
Concentric tube robots (CTRs) offer dexterous motion at millimeter scales, enabling minimally invasive procedures through natural orifices. This work presents a coordinated model-b…
Monocular absolute depth estimation from endoscopy via domain-invariant feature learning and latent consistency
Hao Li, Daiwei Lu, Jesse d'Almeida +8
Monocular depth estimation (MDE) is a critical task to guide autonomous medical robots. However, obtaining absolute (metric) depth from an endoscopy camera in surgical scenes is di…
PERSEUS: Perception with Semantic Endoscopic Understanding and SLAM
Ayberk Acar, Fangjie Li, Susheela Sharma Stern +9
Purpose: Natural orifice surgeries minimize the need for incisions and reduce the recovery time compared to open surgery; however, they require a higher level of expertise due to v…
NAVIUS: Navigated Augmented Reality Visualization for Ureteroscopic Surgery
Ayberk Acar, Jumanh Atoum, Peter S. Connor +4
Ureteroscopy is the standard of care for diagnosing and treating kidney stones and tumors. However, current ureteroscopes have a limited field of view, requiring significant experi…
From Monocular Vision to Autonomous Action: Guiding Tumor Resection via 3D Reconstruction
Ayberk Acar, Mariana Smith, Lidia Al-Zogbi +14
Surgical automation requires precise guidance and understanding of the scene. Current methods in the literature rely on bulky depth cameras to create maps of the anatomy, however t…
An Effectiveness Study Across Baseline and Learning-based Force Estimation Methods on the da Vinci Research Kit Si System
Hao Yang, Ayberk Acar, Keshuai Xu +3
Robot-assisted minimally invasive surgery, such as through the da Vinci systems, improves precision and patient outcomes. However, da Vinci systems prior to da Vinci 5, lacked dire…
MeshBrush: Painting the Anatomical Mesh with Neural Stylization for Endoscopy
John J. Han, Ayberk Acar, Nicholas Kavoussi +1
Style transfer is a promising approach to close the sim-to-real gap in medical endoscopy. Rendering synthetic endoscopic videos by traversing pre-operative scans (such as MRI or CT…
Depth Anything in Medical Images: A Comparative Study
John J. Han, Ayberk Acar, Callahan Henry +1
Monocular depth estimation (MDE) is a critical component of many medical tracking and mapping algorithms, particularly from endoscopic or laparoscopic video. However, because groun…