1 citations · 1 across the 6 of their papers we have counts for
13 papers
ZODIAC: Zero-shot Octree-based Diffusion for Anatomical Completion
Miruna-Alexandra Gafencu, Vlad Bratulescu, Yordanka Velikova +2
Recovering the full 3D spine anatomy from intraoperative ultrasound is an ill-posed inverse problem, as the complete structure must be inferred from incomplete and noisy observatio…
ODeform: Learning Continuous 4D Motion for Shape Deformation with Neural ODEs
Yordanka Velikova, Mahdi Saleh, Liming Kuang +1
Modeling continuous object deformation is important for many computer vision and robotics tasks, such as manipulation and simulation. Existing approaches rely on learning-based met…
DefSynUS: Real-time Patient-specific Intrahepatic Vessel Identification via Deformation-Aware CT-US Domain Adaptation
Karl-Philippe Beaudet, Yordanka Velikova, Sidaty El Hadramy +4
Purpose: Laparoscopic ultrasound (LUS) enhances the safety of liver surgery by visualizing intrahepatic vessels in real-time. Still, vessel identification remains difficult due to…
ConceptPose: Training-Free Zero-Shot Object Pose Estimation using Concept Vectors
Liming Kuang, Yordanka Velikova, Mahdi Saleh +3
Object pose estimation is a fundamental task in computer vision and robotics, yet most methods require extensive, dataset-specific training. Concurrently, large-scale vision langua…
Feasibility of Augmented Reality-Guided Robotic Ultrasound with Cone-Beam CT Integration for Spine Procedures
Tianyu Song, Felix Pabst, Feng Li +5
Accurate needle placement in spine interventions is critical for effective pain management, yet it depends on reliable identification of anatomical landmarks and careful trajectory…
Node-RF: Learning Generalized Continuous Space-Time Scene Dynamics with Neural ODE-based NeRFs
Hiran Sarkar, Liming Kuang, Yordanka Velikova +1
Predicting scene dynamics from visual observations is challenging. Existing methods capture dynamics only within observed boundaries failing to extrapolate far beyond the training…