82 citations · 120 across the 4 of their papers we have counts for
4 papers
Lesion-Aware Generative Artificial Intelligence for Virtual Contrast-Enhanced Mammography in Breast Cancer
Aurora Rofena, Arianna Manchia, Claudia Lucia Piccolo +3
Contrast-Enhanced Spectral Mammography (CESM) is a dual-energy mammographic technique that improves lesion visibility through the administration of an iodinated contrast agent. It…
Augmented Intelligence for Multimodal Virtual Biopsy in Breast Cancer Using Generative Artificial Intelligence
Aurora Rofena, Claudia Lucia Piccolo, Bruno Beomonte Zobel +2
Full-Field Digital Mammography (FFDM) is the primary imaging modality for routine breast cancer screening; however, its effectiveness is limited in patients with dense breast tissu…
A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications
Valerio Guarrasi, Fatih Aksu, Camillo Maria Caruso +4
Deep learning has revolutionized biomedical research by providing sophisticated methods to handle complex, high-dimensional data. Multimodal deep learning (MDL) further enhances th…
A Deep Learning Approach for Virtual Contrast Enhancement in Contrast Enhanced Spectral Mammography
Aurora Rofena, Valerio Guarrasi, Marina Sarli +4
Contrast Enhanced Spectral Mammography (CESM) is a dual-energy mammographic imaging technique that first needs intravenously administration of an iodinated contrast medium; then, i…