23 citations · 27 across the 9 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…
Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge
Lemuel Puglisi, Daniel C. Alexander, Daniele Ravì
In this work, we introduce Brain Latent Progression (BrLP), a novel spatiotemporal disease progression model based on latent diffusion. BrLP is designed to predict the evolution of…