Libertario Demi

Associate Professor

University of Trento

Italy

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Libertario Demi is an Associate Professor at the University of Trento, Italy. His research focuses on high frame rate imaging, deep learning applications in ultrasound diagnostics, and the development of innovative techniques for ultrasound data generation and analysis. Recent publications include studies on synthetic lung ultrasound data, high contrast ultrafast imaging, and automated classification of neonatal lung ultrasound.

Libertario Demi

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Articles (21)

Coherent Plane Wave Compounding combined with Euclidean distance transform for high frame rate and high contrast ultrafast imaging

Synthetic Lung Ultrasound Data Generation Using Autoencoder With Generative Adversarial Network

Mitigating high frame rate demands in shear wave elastography using radial basis function-based reconstruction: An experimental phantom study

FLUEnT: Transformer for detecting lung consolidations in videos using fused lung ultrasound encodings

Time Efficient Ultrasound Localization Microscopy Based on A Novel Radial Basis Function 2D Interpolation

Curated and Annotated Dataset of Lung US Images in Zambian Children with Clinical Pneumonia

Automatic segmentation of 2D echocardiography ultrasound images by means of generative adversarial network

Lung Ultrasound Spectroscopy Applied to the Differential Diagnosis of Pulmonary Diseases: an in vivo multicenter clinical study

A Novel 2x2D Radial Basis Function-Based Interpolation for Short Acquisition Time and Relaxed Frame Rate Ultrasound Localization Microscopy

Deep learning approaches for automated classification of neonatal lung ultrasound with assessment of human-to-AI interrater agreement

Increasing frame rate of echocardiography based on a novel 2D spatio-temporal meshless interpolation

Human‐to‐AI Interrater Agreement for Lung Ultrasound Scoring in COVID‐19 Patients

Best Practice Recommendations for the Safe use of Lung Ultrasound

New International Guidelines and Consensus on the Use of Lung Ultrasound

High Frame Rate Ultrasound Imaging by Means of Tensor Completion: Application to Echocardiography

A two-dimensional angular interpolation based on radial basis functions for high frame rate ultrafast imaging

State of the Art in Lung Ultrasound, Shifting from Qualitative to Quantitative Analyses

Lung Ultrasound in COVID‐19 and Post‐COVID‐19 Patients, an Evidence‐Based Approach

LUS for COVID‐19 Pneumonia: Flexible or Reproducible Approach?

Deep Learning-Based Classification of Reduced Lung Ultrasound Data From COVID-19 Patients

Integrating Domain Knowledge Into Deep Networks for Lung Ultrasound With Applications to COVID-19

Collaborators (4)

Margrit Betke

Marie Muller

Sajjad Afrakhteh

Giovanni Iacca

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