papers

Publications (16)

cs.CV2026

Touchless Intraoperative Image Access System Based on Vision-Based Hand Tracking

Yin Lin, Domenico Aquino, Alberto Redaelli +3

Touchless interaction with medical images is becoming increasingly important in the surgical field, where sterility and continuity of the operational workflow are essential require…

q-bio.TO2022

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…

cs.HC2026

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…

physics.med-ph2017

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…

cs.SD2025

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…

q-bio.QM2025

Deep vectorised operators for pulsatile hemodynamics estimation in coronary arteries from a steady-state prior

Julian Suk, Guido Nannini, Patryk Rygiel +4

Cardiovascular hemodynamic fields provide valuable medical decision markers for coronary artery disease. Computational fluid dynamics (CFD) is the gold standard for accurate, non-i…

physics.med-ph2024

An automated and time efficient framework for simulation of coronary blood flow under steady and pulsatile conditions

Guido Nannini, Simone Saitta, Luca Mariani +5

Fractional flow reserve (FFR) is the gold standard for diagnosing coronary artery disease (CAD). FFRCT uses computational fluid dynamics (CFD) to evaluate FFR non-invasively by sim…

q-bio.QM2023

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…

cs.CV2026

Radiomics- and Clinical Feature-Driven Prediction of Volumetric Response in Skull-Base Meningioma after CyberKnife Radiosurgery

Yin Lin, Elena De Martin, Giacomo Conte +6

Skull-base meningiomas are often characterized by favorable long-term prognosis, yet their anatomical complexity and proximity to critical neurovascular structures make treatment s…

eess.IV2025

Learning Hemodynamic Scalar Fields on Coronary Artery Meshes: A Benchmark of Geometric Deep Learning Models

Guido Nannini, Julian Suk, Patryk Rygiel +7

Coronary artery disease, caused by the narrowing of coronary vessels due to atherosclerosis, is the leading cause of death worldwide. The diagnostic gold standard, fractional flow…

cs.CV2024

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…

cs.CV2025

Glioblastoma Overall Survival Prediction With Vision Transformers

Yin Lin, Riccardo Barbieri, Domenico Aquino +5

Glioblastoma is one of the most aggressive and common brain tumors, with a median survival of 10-15 months. Predicting Overall Survival (OS) is critical for personalizing treatment…

cs.SE2026

A Scalable AI-Powered System for Explainable Machine Learning Pipelines in Brain Tumor

Yin Lin, Elena De Martin, Giacomo Conte +6

The paper introduces a web‑based visual analytics platform that integrates cohort management, radiomic feature extraction, and guarded inference with pre‑trained machine learning m…

#brain tumor analysis#radiomics#visual analytics#explainable ai
eess.IV2025

Pericoronary adipose tissue attenuation as a predictor of functional severity of coronary stenosis

Marta Pillitteri, Guido Nannini, Simone Saitta +5

Objective: This study aims to evaluate the functional significance of coronary stenosis by analyzing low-level radiomic features of the pericoronary adipose tissue (PCAT) surroundi…

cs.RO2024

Augmented Reality and Human-Robot Collaboration Framework for Percutaneous Nephrolithotomy: System Design, Implementation, and Performance Metrics

Junling Fu, Matteo Pecorella, Elisa Iovene +5

During Percutaneous Nephrolithotomy (PCNL) operations, the surgeon is required to define the incision point on the patient's back, align the needle to a pre-planned path, and perfo…

eess.IV2023

Implicit neural representations for unsupervised super-resolution and denoising of 4D flow MRI

Simone Saitta, Marcello Carioni, Subhadip Mukherjee +2

4D flow MRI is a non-invasive imaging method that can measure blood flow velocities over time. However, the velocity fields detected by this technique have limitations due to low r…