Workshop on Computer Vision and Generative Models for Medical Imaging

Held in conjunction with ICIAP 2025

September 15 or 16 (TBC), 2025

Exploring innovative AI applications at the intersection of computer vision, generative models, and medical imaging.

Submit Your Paper

Submission Deadline: June 14, 2025

Overview

This workshop focuses on the intersection of computer vision, generative models, and medical imaging, exploring innovative AI applications in healthcare. It aims to bring together researchers, clinicians, and industry professionals to present and discuss novel methodologies that address key challenges in medical imaging and healthcare. In particular, the workshop highlights the transformative potential of generative models and advanced computational techniques in areas such as disease progression modeling, synthetic data generation, multimodal data integration, and both imaging and non-imaging diagnostics. These approaches have the potential to revolutionize precision medicine by improving diagnostic accuracy, enhancing personalized care, and addressing data scarcity issues in clinical research.

Call for Papers: Share Your Innovations!

We invite you to submit your cutting-edge research to the Workshop on Computer Vision and Generative Models for Medical Imaging (CVGMMI), held in conjunction with ICIAP 2025. Join us in exploring the transformative potential of AI in healthcare!

Areas of Interest

We welcome original contributions related (but not limited) to:

  • Novel Deep Learning Architectures for Medical Data Analysis & Synthesis
  • Generative Models for Predictive Healthcare & Disease Modeling
  • Multimodal Learning (Imaging, Clinical, Genetic, etc.)
  • Privacy-Preserving Techniques for Healthcare Data
  • Explainable AI (XAI) for Medical Image Interpretation
  • Clinical Applications & Impact of AI-Powered Medical Imaging
  • Natural Language Processing (NLP) for Clinical Narratives
  • Ethical Considerations in AI-Driven Healthcare

Submission Guidelines

  • 📄 Format & Length: Papers must be in PDF format and not exceed 12 pages (including references). Please use the official LNCS template (Overleaf).
  • ✨ Originality: Submissions must be original work, not previously published or under review elsewhere.
  • 💻 Submission Platform: Submit your paper via the EasyChair system.
  • 📚 Proceedings: Accepted papers will be published in the Springer Lecture Notes in Computer Science (LNCS) series (indexed in Web of Science, Scopus, etc.).

Mark Your Calendar: Important Dates

Submission Deadline:
June 14, 2025
Notification to Authors:
July 3, 2025
Camera-Ready Due:
July 10, 2025
Workshop:
Sept 15 or 16, 2025 (TBC)

Organizers

Prof. Daniele Ravì
Prof. Daniele Ravì (Chair)
University of Messina & University College London

Background: Associate Professor with extensive expertise in AI for medical imaging, image-guided surgery, disease progression modeling, and smart sensing. BSc/MSc CompSci, PhD CompVision (UniCT). Postdoc at Imperial/UCL, industry experience. Published >18 Q1 journal papers, holds patent. Secured >£500k in grants.
Research Interests: Computer vision, ML, image-guided surgery, smart sensing (MRI, endomicroscopy, endoscopy, hyperspectral), clinical translation, CNNs, GANs, VAEs.

dravi@unime.it d.ravi@ucl.ac.uk
Lemuel Puglisi
Lemuel Puglisi
University of Catania & University College London & Queen Square Analytics

Background: Strong background in CS, AI, medical imaging. Focus on disease progression modeling, brain age estimation, medical image analysis. BSc/MSc CompSci (UniCT, Hons). PhD student (UniCT) since 2023.
Experience: Imaging Research Scientist at Queen Square Analytics (UCL spin-out) since 2022 (medical image analysis for clinical trials). Visiting researcher at UCL Hawkes Institute (MANIFOLD lab) since Feb 2024. Publications at MICCAI, MIDL, and Medical Image Analysis (Q1).

lemuel.puglisi@phd.unict.it
Giulio Minore
Giulio Minore
University College London

Background: Strong background in physics, AI, and medical imaging. Focus on ML techniques for quantitative MRI parameter estimation and medical image analysis. MSci Physics, MSc Machine Learning, MRes Medical Imaging. PhD student in Medical Imaging at the Computational Imaging Group (CIG-UCL).
Research Interests: Research Interests: Quantitative MRI (qMRI), deep learning, MRI biomarkers, computational modeling, medical image analysis. Publications at MICCAI (2021), IPMI (2025).

giulio.minore.17@ucl.ac.uk

Invited Speakers

Prof. Antonio Celesti
Prof. Antonio Celesti
University of Messina

(Confirmed)

Full Professor of Computer Science at UniMe. Research focuses on distributed systems, cloud/edge computing, IoT, and ML applications in healthcare. Extensive experience in cloud architectures, security, resource management in federated cloud environments.

Not Confirmed
Coming Soon
N/A

(Tentative)

N/A

Not Confirmed
Coming Soon
N/A

(Tentative)

N/A

Venue

Sapienza University of Rome

The workshop, held in conjunction with ICIAP 2025, will take place at the prestigious Sapienza University of Rome, located in the heart of the eternal city.

Established in 1303, Sapienza is one of the oldest universities in the world and consistently ranks among the top universities in Italy and Europe. Its historic campus provides an inspiring and vibrant setting for collaboration and discussion.

Learn more about Sapienza University

Placeholder image of Sapienza University of Rome campus

Program Committee