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cs.CV2018
Training of a Skull-Stripping Neural Network with efficient data augmentation
Gabriele Valvano, Nicola Martini, Andrea Leo +4
Skull-stripping methods aim to remove the non-brain tissue from acquisition of brain scans in magnetic resonance (MR) imaging. Although several methods sharing this common purpose…
cs.CV2018
Unsupervised Data Selection for Supervised Learning
Gabriele Valvano, Andrea Leo, Daniele Della Latta +4
Recent research put a big effort in the development of deep learning architectures and optimizers obtaining impressive results in areas ranging from vision to language processing.…
cs.CV2018
Synthetic contrast enhancement in cardiac CT with Deep Learning
Gianmarco Santini, Lorena M. Zumbo, Nicola Martini +6
In Europe the 20% of the CT scans cover the thoracic region. The acquired images contain information about the cardiovascular system that often remains latent due to the lack of co…