8 papers
Cross Modality Image Translation In Medical Imaging Using Generative Frameworks
Giulia Romoli, Alessia Capoccia, Filippo Ruffini +20
Medical image-to-image (I2I) translation enables virtual scanning, i.e. the synthesis of a target imaging modality from a source one without additional acquisitions. Despite growin…
Longitudinal NSCLC Treatment Progression via Multimodal Generative Models
Massimiliano Mantegna, Elena Mulero Ayllón, Alice Natalina Caragliano +10
Predicting tumor evolution during radiotherapy is a clinically critical challenge, particularly when longitudinal changes are driven by both anatomy and treatment. In this work, we…
Sample-Aware Test-Time Adaptation for Medical Image-to-Image Translation
Irene Iele, Francesco Di Feola, Valerio Guarrasi +1
Image-to-image translation has emerged as a powerful technique in medical imaging, enabling tasks such as image denoising and cross-modality conversion. However, it suffers from li…
XGeM: A Multi-Prompt Foundation Model for Multimodal Medical Data Generation
Daniele Molino, Francesco Di Feola, Eliodoro Faiella +5
The adoption of Artificial Intelligence in medical imaging holds great promise, yet it remains hindered by challenges such as data scarcity, privacy concerns, and the need for robu…
Any-to-Any Vision-Language Model for Multimodal X-ray Imaging and Radiological Report Generation
Daniele Molino, Francesco di Feola, Linlin Shen +2
Generative models have revolutionized Artificial Intelligence (AI), particularly in multimodal applications. However, adapting these models to the medical domain poses unique chall…
Texture-Aware StarGAN for CT data harmonisation
Francesco Di Feola, Ludovica Pompilio, Cecilia Assolito +2
Computed Tomography (CT) plays a pivotal role in medical diagnosis; however, variability across reconstruction kernels hinders data-driven approaches, such as deep learning models,…