2 citations · 4 across the 17 of their papers we have counts for
17 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…
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…
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…
US-X Complete: A Multi-Modal Approach to Anatomical 3D Shape Recovery
Miruna-Alexandra Gafencu, Yordanka Velikova, Nassir Navab +1
Ultrasound offers a radiation-free, cost-effective solution for real-time visualization of spinal landmarks, paraspinal soft tissues and neurovascular structures, making it valuabl…
Shape Completion and Real-Time Visualization in Robotic Ultrasound Spine Acquisitions
Miruna-Alexandra Gafencu, Reem Shaban, Yordanka Velikova +2
Ultrasound (US) imaging is increasingly used in spinal procedures due to its real-time, radiation-free capabilities; however, its effectiveness is hindered by shadowing artifacts t…
Deep Spectral Methods for Unsupervised Ultrasound Image Interpretation
Oleksandra Tmenova, Yordanka Velikova, Mahdi Saleh +1
Ultrasound imaging is challenging to interpret due to non-uniform intensities, low contrast, and inherent artifacts, necessitating extensive training for non-specialists. Advanced…
Diffusion as Sound Propagation: Physics-inspired Model for Ultrasound Image Generation
Marina Domínguez, Yordanka Velikova, Nassir Navab +1
Deep learning (DL) methods typically require large datasets to effectively learn data distributions. However, in the medical field, data is often limited in quantity, and acquiring…
Shape Completion in the Dark: Completing Vertebrae Morphology from 3D Ultrasound
Miruna-Alexandra Gafencu, Yordanka Velikova, Mahdi Saleh +4
Purpose: Ultrasound (US) imaging, while advantageous for its radiation-free nature, is challenging to interpret due to only partially visible organs and a lack of complete 3D infor…
CathFlow: Self-Supervised Segmentation of Catheters in Interventional Ultrasound Using Optical Flow and Transformers
Alex Ranne, Liming Kuang, Yordanka Velikova +2
In minimally invasive endovascular procedures, contrast-enhanced angiography remains the most robust imaging technique. However, it is at the expense of the patient and clinician's…
Implicit Neural Representations for Breathing-compensated Volume Reconstruction in Robotic Ultrasound
Yordanka Velikova, Mohammad Farid Azampour, Walter Simson +2
Ultrasound (US) imaging is widely used in diagnosing and staging abdominal diseases due to its lack of non-ionizing radiation and prevalent availability. However, significant inter…
AiAReSeg: Catheter Detection and Segmentation in Interventional Ultrasound using Transformers
Alex Ranne, Yordanka Velikova, Nassir Navab +1
To date, endovascular surgeries are performed using the golden standard of Fluoroscopy, which uses ionising radiation to visualise catheters and vasculature. Prolonged Fluoroscopic…
Can ultrasound confidence maps predict sonographers' labeling variability?
Vanessa Gonzalez Duque, Leonhard Zirus, Yordanka Velikova +2
Measuring cross-sectional areas in ultrasound images is a standard tool to evaluate disease progress or treatment response. Often addressed today with supervised deep-learning segm…
LOTUS: Learning to Optimize Task-based US representations
Yordanka Velikova, Mohammad Farid Azampour, Walter Simson +2
Anatomical segmentation of organs in ultrasound images is essential to many clinical applications, particularly for diagnosis and monitoring. Existing deep neural networks require…
CACTUSS: Common Anatomical CT-US Space for US examinations
Yordanka Velikova, Walter Simson, Mehrdad Salehi +3
Abdominal aortic aneurysm (AAA) is a vascular disease in which a section of the aorta enlarges, weakening its walls and potentially rupturing the vessel. Abdominal ultrasound has b…