199 citations · 199 across the 5 of their papers we have counts for
5 papers
FedCC: A Low-Resource Federated Adaptation of Foundation Models for Robust Corpus Callosum localization in Fetal Ultrasound Images
Alessandro Di Matteo, Sara Moccia, Giuseppe Rizzo +5
Accurate localization of the corpus callosum (CC) in fetal ultrasound (US) images is crucial for the early identification of neurodevelopmental abnormalities. However, this task re…
From Kellgren-Lawrence to Calcium Pyrophosphate Crystal Deposition: A Soft-Labelling Framework for Knee Osteoarthritis Assessmen
Francisco Bérchez-Moreno, Riccardo Rosati, Maria Chiara Fiorentino +6
Background and objective. Conventional Deep Learning (DL) approaches for Knee Osteoarthritis (KOA) grading rely on one-hot labels, which fail to capture both the ordinal uncertaint…
Challenging DINOv3 Foundation Model under Low Inter-Class Variability: A Case Study on Fetal Brain Ultrasound
Edoardo Conti, Riccardo Rosati, Lorenzo Federici +2
Purpose: This study provides the first comprehensive evaluation of foundation models in fetal ultrasound (US) imaging under low inter-class variability conditions. While recent vis…
A Federated Learning Framework for Stenosis Detection
Mariachiara Di Cosmo, Giovanna Migliorelli, Matteo Francioni +6
This study explores the use of Federated Learning (FL) for stenosis detection in coronary angiography images (CA). Two heterogeneous datasets from two institutions were considered:…
A Review on Deep-Learning Algorithms for Fetal Ultrasound-Image Analysis
Maria Chiara Fiorentino, Francesca Pia Villani, Mariachiara Di Cosmo +2
Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US) fetal images. Despite a large number of survey papers already present in this field, most of…