30 citations · 50 across the 9 of their papers we have counts for
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eess.IV2024★ 10 cited
Multi-Dataset Multi-Task Learning for COVID-19 Prognosis
Filippo Ruffini, Lorenzo Tronchin, Zhuoru Wu +4
In the fight against the COVID-19 pandemic, leveraging artificial intelligence to predict disease outcomes from chest radiographic images represents a significant scientific aim. T…
eess.IV2024★ 1 cited
Multi-Scale Texture Loss for CT denoising with GANs
Francesco Di Feola, Lorenzo Tronchin, Valerio Guarrasi +1
Generative Adversarial Networks (GANs) have proved as a powerful framework for denoising applications in medical imaging. However, GAN-based denoising algorithms still suffer from…