activity
20242026
collaborators

7 papers

cs.CV2026

GenTract: Generative Global Tractography

Alec Sargood, Lemuel Puglisi, Elinor Thompson +2

Tractography is the process of inferring the trajectories of white-matter pathways in the brain from diffusion magnetic resonance imaging (dMRI). Local tractography methods, which…

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.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…

eess.IV2025

CoCoLIT: ControlNet-Conditioned Latent Image Translation for MRI to Amyloid PET Synthesis

Alec Sargood, Lemuel Puglisi, James H. Cole +3

Synthesizing amyloid PET scans from the more widely available and accessible structural MRI modality offers a promising, cost-effective approach for large-scale Alzheimer's Disease…

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…

cs.CV2025

Brain Latent Progression: Individual-based Spatiotemporal Disease Progression on 3D Brain MRIs via Latent Diffusion

Lemuel Puglisi, Daniel C. Alexander, Daniele Ravì

The growing availability of longitudinal Magnetic Resonance Imaging (MRI) datasets has facilitated Artificial Intelligence (AI)-driven modeling of disease progression, making it po…