Lemuel Puglisi

According to our database, Lemuel Puglisi authored at least 8 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

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

Andrea Moschetto, Lemuel Puglisi, Alec Sargood, Pierluigi Dell'Acqua, Francesco Guarnera, Sebastiano Battiato, Daniele Ravì

CoRR, July, 2025

Brain Latent Progression: Individual-based spatiotemporal disease progression on 3D Brain MRIs via latent diffusion.

Lemuel Puglisi, Daniel C. Alexander, Daniele Ravì

Medical Image Anal., 2025

2024

An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training.

Daniele Ravì, Frederik Barkhof, Daniel C. Alexander, Lemuel Puglisi, Geoffrey J. M. Parker, Arman Eshaghi

Medical Image Anal., January, 2024

Enhancing Spatiotemporal Disease Progression Models via Latent Diffusion and Prior Knowledge.

Lemuel Puglisi, Daniel C. Alexander, Daniele Ravì

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

Efficient Atrophy Mapping: A Single-Step U-Net Approach for Rapid Brain Change Estimation.

Riccardo Raciti, Alessia Rondinella, Lemuel Puglisi, Francesco Guarnera, Daniele Ravì, Sebastiano Battiato

Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2024

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

Lemuel Puglisi, Alessia Rondinella, Linda De Meo, Francesco Guarnera, Sebastiano Battiato, Daniele Ravì

Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2024

Industrial Machines Health Prognosis Using a Transformer-Based Framework.

David J. Poland, Lemuel Puglisi, Daniele Ravì

Proceedings of the IEEE International Conference on Metrology for eXtended Reality, 2024

2023

DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification.

Lemuel Puglisi, Arman Eshaghi, Geoff J. M. Parker, Frederik Barkhof, Daniel C. Alexander, Daniele Ravì

Proceedings of the Medical Imaging with Deep Learning, 2023