Emiliano Votta

Associate Professor

Politecnico di Milano

Italy

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Emiliano Votta is an Associate Professor at Politecnico di Milano, Italy. His research focuses on advanced imaging and robotics in cardiovascular interventions, including automated localization techniques in echocardiography and telerobotic systems for transesophageal procedures. Recent publications highlight the application of deep learning in cardiac analysis and the impact of structural factors on heart procedures. He contributes significantly to the field with a strong emphasis on innovation in transcatheter heart interventions.

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2021

Collaborators (3)

Paolo Zunino

University of Pittsburgh

UNITED STATES

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alberto redaelli

Full Professor

Politecnico di Milano

ITALY

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Selene Pirola

Assistant Professor

Delft University of Technology

NETHERLANDS

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Emiliano Votta

Research Interests

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About

Articles (20)

MitraClip device automated localization in 3D transesophageal echocardiography via deep learning

Planning transcatheter pulmonary valve implantation in the dysfunctional native RVOT: A semi-automated pipeline for dynamic analysis based on 4D-CT imaging

Automatic 4D mitral valve segmentation from transesophageal echocardiography: a semi-supervised learning approach

Design and Hysteresis Compensation of a Telerobotic System for Transesophageal Echocardiography

Ascending aorta over-angulation is a risk factor for acute type A aortic dissection: evidence from advanced finite element simulations

Current and future applications of robotics in structural heart interventions

Imitation Learning for Path Planning in Cardiac Percutaneous Interventions

Impact of aortic landing zone geometry on TAVI implantation depth: Comparison between ACURATE neo2 and Portico/Evolut

Intracavitary blood flow dynamics in the systemic right ventricle after atrial switch operation: a shift from transverse to longitudinal systolic pattern

A Deep Learning-Based Fully Automated Pipeline for Regurgitant Mitral Valve Anatomy Analysis From 3D Echocardiography

A CT-based deep learning system for automatic assessment of aortic root morphology for TAVI planning

Data-driven generation of 4D velocity profiles in the aneurysmal ascending aorta

A Deep Learning-Based and Fully Automated Pipeline for Thoracic Aorta Geometric Analysis and Planning for Endovascular Repair from Computed Tomography

Comparison of Four-Dimensional Magnetic Resonance Imaging Analysis of Left Ventricular Fluid Dynamics and Energetics in Ischemic and Restrictive Cardiomyopathies

Fast Approximate Quantification of Endovascular Stent Graft Displacement Forces in the Bovine Aortic Arch Variant

Non-invasive estimation of vascular compliance and distensibility in the arm vessels: a novel ultrasound-based protocol

Prognostic value of left atrial strain quantification from 2D ultrasound imaging in post-ischemic heart failure patients: evidence from the REMODEL-HF study

Three-dimensional printing, holograms, computational modelling, and artificial intelligence for adult congenital heart disease care: an exciting future

A surrogate model for plaque modeling in carotids based on Robin conditions calibrated by cine MRI data

4D flow evaluation of blood non-Newtonian behavior in left ventricle flow analysis

Collaborators (3)

Paolo Zunino

alberto redaelli

Selene Pirola

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