Related papers: 4D Vessel Reconstruction for Benchtop Thrombectomy…
Background: Four-corner arthrodesis, which involves fusing four carpal bones while removing the scaphoid bone, is a standard surgery for the treatment of advanced stages of wrist arthritis. Nowadays, it can be performed using a dorsal…
Depth estimation is a fundamental task in computer vision with diverse applications. Recent advancements in deep learning have led to powerful depth foundation models (DFMs), yet their evaluation remains challenging due to inconsistencies…
Mesh deformation plays a pivotal role in many 3D vision tasks including dynamic simulations, rendering, and reconstruction. However, defining an efficient discrepancy between predicted and target meshes remains an open problem. A prevalent…
This paper presents a novel neural network architecture for the purpose of pervasive visualisation of a 3D human upper limb musculoskeletal system model. Bringing simulation capabilities to resource-poor systems like mobile devices is of…
To shorten the door-to-puncture time for better treating patients with acute ischemic stroke, it is highly desired to obtain quantitative cerebral perfusion images using C-arm cone-beam computed tomography (CBCT) equipped in the…
We performed numerical simulations of blood flow in arteries with a variable stiffness and cross-section at rest using a finite volume method coupled with a hydrostatic reconstruction of the variables at the interface of each mesh cell. The…
Thrombosis involves processes spanning large-scale fluid flow to sub-cellular events such as platelet activation. Traditional CFD approaches often treat blood as a continuum, which can limit their ability to capture these microscale…
The 3D reconstruction of simultaneous localization and mapping (SLAM) is an important topic in the field for transport systems such as drones, service robots and mobile AR/VR devices. Compared to a point cloud representation, the 3D…
Measuring the blood pressure waveform is becoming a more frequently studied area. The development of sensor technologies opens many new ways to be able to measure high-quality signals. The development of such an aim-specific sensor can be…
Blood vessel networks in the brain play a crucial role in stroke research, where understanding their topology is essential for analyzing blood flow dynamics. However, extracting detailed topological vessel network information from…
We investigate the reconstruction of a turbulent flow field in the atmospheric boundary layer from a time series of lidar measurements, using Large-Eddy Simulations (LES) and a 4D-Var data assimilation algorithm. This leads to an…
Objective: Use of a vascular punch to produce circular heel and toe arteriotomies for femoral endarterectomy with patch angioplasty is a novel technique. This study investigated the plausibility of this approach and the mechanical…
4D head capture aims to generate dynamic topological meshes and corresponding texture maps from videos, which is widely utilized in movies and games for its ability to simulate facial muscle movements and recover dynamic textures in…
OBJECTIVE: This study evaluated the accuracy in localisation and distribution of real-time three-dimensional (4-D) ultrasound-guided biopsies on a prostate phantom. METHODS: A prostate phantom was created. A three-dimensional real-time…
Predicting the long-term success of endovascular interventions in the clinical management of cerebral aneurysms requires detailed insight into the patient-specific physiological conditions. In this work, we not only propose numerical…
Purpose: Enabling a comprehensive and robust assessment of carotid artery plaques in 3D through extraction and visualization of quantitative plaque parameters. These parameters have potential applications in stroke risk analysis, evaluation…
Four-dimensional (4D; 3D + time) microscopic imaging has emerged as a powerful technique for investigating dynamic phenomena in complex systems, enabling direct visualization of structural evolution in space and time. However, when pushing…
We propose Deep-Motion-Net: an end-to-end graph neural network (GNN) architecture that enables 3D (volumetric) organ shape reconstruction from a single in-treatment kV planar X-ray image acquired at any arbitrary projection angle.…
Deep Learning (DL) and specifically CNN models have become a de facto method for a wide range of vision tasks, outperforming traditional machine learning (ML) methods. Consequently, they drew a lot of attention in the neuroimaging field in…
Reconstruction of the mandible is one of the most common challenges facing maxillofacial surgeons. The mandible plays a major role in supporting the teeth inside the mouth. This work aims to develop a proposed methodology for improving…