activity
20202026
most citedBoosting multiple sclerosis lesion segmentation through attention mechanism

75 citations · 86 across the 13 of their papers we have counts for

collaborators

16 papers

cs.CV2026

Auditing Patient Privacy in Medical Generative Models: Scalable Memorization Detection with DeepSSIM++

Antonio Scardace, Francesco Guarnera, Sebastiano Battiato +1

While deep generative models offer new opportunities for medical image synthesis and data sharing, their ability to memorize and reproduce training samples raises serious concerns…

cs.CV2026

The K-Space Signature: Frequency-Domain Representation Learning for Medical Deepfake Detection

Riccardo Raciti, Francesco Guarnera, Francesco Rundo +2

In medical imaging, generative models are increasingly deployed to synthesize realistic data and augment limited datasets. Unfortunately, while beneficial for privacy-preserving da…

eess.IV2026

Reinforcing the Weakest Links: Modernizing SIENA with Targeted Deep Learning Integration

Riccardo Raciti, Lemuel Puglisi, Francesco Guarnera +2

Percentage Brain Volume Change (PBVC) derived from Magnetic Resonance Imaging (MRI) is a widely used biomarker of brain atrophy, with SIENA among the most established methods for i…

cs.CV2026

SynthForensics: Benchmarking and Evaluating People-Centric Synthetic Video Deepfakes

Roberto Leotta, Salvatore Alfio Sambataro, Claudio Vittorio Ragaglia +5

Modern T2V/I2V generators synthesize people increasingly hard to distinguish from authentic footage, while current evaluation suites lag: legacy benchmarks target manipulation-base…

cs.CV2025

Temporally-Aware Diffusion Model for Brain Progression Modelling with Bidirectional Temporal Regularisation

Mattia Litrico, Francesco Guarnera, Mario Valerio Giuffrida +2

Generating realistic MRIs to accurately predict future changes in the structure of brain is an invaluable tool for clinicians in assessing clinical outcomes and analysing the disea…

cs.CV2025

A Novel Metric for Detecting Memorization in Generative Models for Brain MRI Synthesis

Antonio Scardace, Lemuel Puglisi, Francesco Guarnera +2

Deep generative models have emerged as a transformative tool in medical imaging, offering substantial potential for synthetic data generation. However, recent empirical studies hig…

cs.CV2025

Benchmarking GANs, Diffusion Models, and Flow Matching for T1w-to-T2w MRI Translation

Andrea Moschetto, Lemuel Puglisi, Alec Sargood +4

Magnetic Resonance Imaging (MRI) enables the acquisition of multiple image contrasts, such as T1-weighted (T1w) and T2-weighted (T2w) scans, each offering distinct diagnostic insig…

eess.IV2024

ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation -- Methods and Results

Alessia Rondinella, Francesco Guarnera, Elena Crispino +5

This report summarizes the outcomes of the ICPR 2024 Competition on Multiple Sclerosis Lesion Segmentation (MSLesSeg). The competition aimed to develop methods capable of automatic…

eess.IV2024★ 2 cited

SynthBA: Reliable Brain Age Estimation Across Multiple MRI Sequences and Resolutions

Lemuel Puglisi, Alessia Rondinella, Linda De Meo +3

Brain age is a critical measure that reflects the biological ageing process of the brain. The gap between brain age and chronological age, referred to as brain PAD (Predicted Age D…

eess.IV2024

TADM: Temporally-Aware Diffusion Model for Neurodegenerative Progression on Brain MRI

Mattia Litrico, Francesco Guarnera, Valerio Giuffirda +2

Generating realistic images to accurately predict changes in the structure of brain MRI is a crucial tool for clinicians. Such applications help assess patients' outcomes and analy…

cs.CV2024★ 1 cited

On the exploitation of DCT statistics for cropping detectors

Claudio Vittorio Ragaglia, Francesco Guarnera, Sebastiano Battiato

{The study of frequency components derived from Discrete Cosine Transform (DCT) has been widely used in image analysis. In recent years it has been observed that significant inform…

eess.IV2023★ 75 cited

Boosting multiple sclerosis lesion segmentation through attention mechanism

Alessia Rondinella, Elena Crispino, Francesco Guarnera +7

Magnetic resonance imaging is a fundamental tool to reach a diagnosis of multiple sclerosis and monitoring its progression. Although several attempts have been made to segment mult…

eess.IV2023★ 6 cited

Early detection of hip periprosthetic joint infections through CNN on Computed Tomography images

Francesco Guarnera, Alessia Rondinella, Oliver Giudice +6

Early detection of an infection prior to prosthesis removal (e.g., hips, knees or other areas) would provide significant benefits to patients. Currently, the detection task is carr…

eess.IV2023

UniCT DMI Solution for 3rd COV19D Competition on COVID-19 Detection through attention-based CNN for CT Scan

Alessia Rondinella, Francesco Guarnera, Oliver Giudice +3

This paper presents our solution for the first challenge of the 3rd Covid-19 competition, which is part of the "AI-enabled Medical Image Analysis Workshop" organized by IEEE Intern…

eess.IV2020★ 2 cited

In-Depth DCT Coefficient Distribution Analysis for First Quantization Estimation

Sebastiano Battiato, Oliver Giudice, Francesco Guarnera +1

The exploitation of traces in JPEG double compressed images is of utter importance for investigations. Properly exploiting such insights, First Quantization Estimation (FQE) could…

cs.CV2020

Animated GIF optimization by adaptive color local table management

Oliver Giudice, Dario Allegra, Francesco Guarnera +2

After thirty years of the GIF file format, today is becoming more popular than ever: being a great way of communication for friends and communities on Instant Messengers and Social…