82 citations · 380 across the 53 of their papers we have counts for
5 papers · 1 filter
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…
LatentAugment: Data Augmentation via Guided Manipulation of GAN's Latent Space
Lorenzo Tronchin, Minh H. Vu, Paolo Soda +1
Data Augmentation (DA) is a technique to increase the quantity and diversity of the training data, and by that alleviate overfitting and improve generalisation. However, standard D…
A Deep Learning Approach for Overall Survival Prediction in Lung Cancer with Missing Values
Camillo Maria Caruso, Valerio Guarrasi, Sara Ramella +1
In the field of lung cancer research, particularly in the analysis of overall survival (OS), artificial intelligence (AI) serves crucial roles with specific aims. Given the prevale…
MATNet: Multi-Level Fusion Transformer-Based Model for Day-Ahead PV Generation Forecasting
Matteo Tortora, Francesco Conte, Gianluca Natrella +1
Accurate forecasting of renewable generation is crucial to facilitate the integration of Renewable Energy Sources into the power system. Focusing on photovoltaic (PV) units, foreca…
A comparative study between paired and unpaired Image Quality Assessment in Low-Dose CT Denoising
Francesco Di Feola, Lorenzo Tronchin, Paolo Soda
The current deep learning approaches for low-dose CT denoising can be divided into paired and unpaired methods. The former involves the use of well-paired datasets, whilst the latt…