21 citations · 36 across the 4 of their papers we have counts for
4 papers
Distributed Learning Approaches for Automated Chest X-Ray Diagnosis
Edoardo Giacomello, Michele Cataldo, Daniele Loiacono +1
Deep Learning has established in the latest years as a successful approach to address a great variety of tasks. Healthcare is one of the most promising field of application for Dee…
Image Embedding and Model Ensembling for Automated Chest X-Ray Interpretation
Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono +1
Chest X-ray (CXR) is perhaps the most frequently-performed radiological investigation globally. In this work, we present and study several machine learning approaches to develop au…
Brain MRI Tumor Segmentation with Adversarial Networks
Edoardo Giacomello, Daniele Loiacono, Luca Mainardi
Deep Learning is a promising approach to either automate or simplify several tasks in the healthcare domain. In this work, we introduce SegAN-CAT, an approach to brain tumor segmen…
DOOM Level Generation using Generative Adversarial Networks
Edoardo Giacomello, Pier Luca Lanzi, Daniele Loiacono
We applied Generative Adversarial Networks (GANs) to learn a model of DOOM levels from human-designed content. Initially, we analysed the levels and extracted several topological f…