20 citations · 45 across the 23 of their papers we have counts for
13 papers · 1 filter
Deformable CT-US Registration via Anatomy-Aware Implicit Neural Representations
Agnieszka Lach, Magdalena Wysocki, Feng Li +7
Slice-to-volume registration between ultrasound (US) and preoperative computed tomography (CT) imaging would enhance many minimally invasive interventions, for example by locating…
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…
Multivariate Gaussian NeRF for Wide Field-of-View Ultrasound Reconstruction
Patris Valera, Magdalena Wysocki, Felix Duelmer +4
Wide Field-of-View (WFoV) reconstruction enhances 3D ultrasound imaging by providing valuable anatomical context for segmentation models and visualization. Clinical ultrasound volu…
UltraG-Ray: Physics-Based Gaussian Ray Casting for Novel Ultrasound View Synthesis
Felix Duelmer, Jakob Klaushofer, Magdalena Wysocki +2
Novel view synthesis (NVS) in ultrasound has gained attention as a technique for generating anatomically plausible views beyond the acquired frames, offering new capabilities for t…
OSCAR: Occupancy-based Shape Completion via Acoustic Neural Implicit Representations
Magdalena Wysocki, Kadir Burak Buldu, Miruna-Alexandra Gafencu +2
Accurate 3D reconstruction of vertebral anatomy from ultrasound is important for guiding minimally invasive spine interventions, but it remains challenging due to acoustic shadowin…
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…
UltrON: Ultrasound Occupancy Networks
Magdalena Wysocki, Felix Duelmer, Ananya Bal +2
In free-hand ultrasound imaging, sonographers rely on expertise to mentally integrate partial 2D views into 3D anatomical shapes. Shape reconstruction can assist clinicians in this…
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…
HyperSORT: Self-Organising Robust Training with hyper-networks
Samuel Joutard, Marijn Stollenga, Marc Balle Sanchez +2
Medical imaging datasets often contain heterogeneous biases ranging from erroneous labels to inconsistent labeling styles. Such biases can negatively impact deep segmentation netwo…
UltraRay: Introducing Full-Path Ray Tracing in Physics-Based Ultrasound Simulation
Felix Duelmer, Mohammad Farid Azampour, Magdalena Wysocki +1
Traditional ultrasound simulators solve the wave equation to model pressure distribution fields, achieving high accuracy but requiring significant computational time and resources.…
Intraoperative Registration by Cross-Modal Inverse Neural Rendering
Maximilian Fehrentz, Mohammad Farid Azampour, Reuben Dorent +7
We present in this paper a novel approach for 3D/2D intraoperative registration during neurosurgery via cross-modal inverse neural rendering. Our approach separates implicit neural…
PHOCUS: Physics-Based Deconvolution for Ultrasound Resolution Enhancement
Felix Duelmer, Walter Simson, Mohammad Farid Azampour +3
Ultrasound is widely used in medical diagnostics allowing for accessible and powerful imaging but suffers from resolution limitations due to diffraction and the finite aperture of…
Uncertainty quantification in non-rigid image registration via stochastic gradient Markov chain Monte Carlo
Daniel Grzech, Mohammad Farid Azampour, Huaqi Qiu +3
We develop a new Bayesian model for non-rigid registration of three-dimensional medical images, with a focus on uncertainty quantification. Probabilistic registration of large imag…