20 citations · 26 across the 9 of their papers we have counts for
9 papers
Evaluation of Augmented Reality-based Intuitive Interface for Robot-Assisted Transesophageal Echocardiography: A User Study
Xiu Zhang*, Matteo Di Mauro*, Sofia Breschi +4
TransEsophageal Echocardiography (TEE) is essential for diagnosing and guiding Structural Heart Disease (SHD) interventions. However, manual TEE manipulation demands significant op…
Physics-driven Sonification for Improving Multisensory Needle Guidance in Percutaneous Epicardial Access
Veronica Ruozzi, Sasan Matinfar, Pasquale Vergara +7
Percutaneous epicardial access (PEA), performed on a beating heart under fluoroscopy, enables arrhythmia treatment. However, advancing a needle toward the thin and moving pericardi…
Catheter Monitoring in Intelligent Endovascular Navigation Systems: Interactive Simulations and Mixed Reality for Enhanced Navigational Awareness
Veronica Ruozzi, Giovanni Battista Regazzo, Maria Chiara Palumbo +7
Purpose: Developing and testing a framework that integrates real-time catheter shape reconstruction, interactive simulations, and mixed reality visualization to enable accurate mon…
BioSonix: Can Physics-Based Sonification Perceptualize Tissue Deformations From Tool Interactions?
Veronica Ruozzi, Sasan Matinfar, Laura Schütz +4
Perceptualizing tool interactions with deformable structures in surgical procedures remains challenging, as unimodal visualization techniques often fail to capture the complexity o…
MitraClip Device Automated Localization in 3D Transesophageal Echocardiography via Deep Learning
Riccardo Munafò, Simone Saitta, Luca Vicentini +7
The MitraClip is the most widely percutaneous treatment for mitral regurgitation, typically performed under the real-time guidance of 3D transesophagel echocardiography (TEE). Howe…
A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning
Simone Saitta, Francesco Sturla, Riccardo Gorla +4
Accurate planning of transcatheter aortic implantation (TAVI) is important to minimize complications, and it requires anatomic evaluation of the aortic root (AR), commonly done thr…
A Deep Learning-Based Fully Automated Pipeline for Regurgitant Mitral Valve Anatomy Analysis From 3D Echocardiography
Riccardo Munafò, Simone Saitta, Giacomo Ingallina +5
Three-dimensional transesophageal echocardiography (3DTEE) is the recommended imaging technique for the assessment of mitral valve (MV) morphology and lesions in case of mitral reg…
Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta
Simone Saitta, Ludovica Maga, Chloe Armour +8
Numerical simulations of blood flow are a valuable tool to investigate the pathophysiology of ascending thoracic aortic aneurysms (ATAA). To accurately reproduce hemodynamics, comp…
Simulation of left ventricle fluid dynamics with mitral regurgitation from magnetic resonance images with fictitious elastic structure regularization
Toni Lassila, Cristiano Malossi, Marco Stevanella +3
Computer modeling can provide quantitative insight into cardiac fluid dynamics phenomena that are not evident from standard imaging tools. We propose a new approach to modeling lef…