activity
20172021
most citedAn automatic deep learning approach for coronary artery calcium segmentation

22 citations · 59 across the 8 of their papers we have counts for

collaborators
Showing 2018Show all

5 papers · 1 filter

physics.app-ph2018★ 18 cited

Optofluidic sensor system with Ge PIN photodetector for CMOS-compatible sensing

Lion Augel, Fritz Berkmann, Daniel Latta +6

Vertical optofluidic biosensors based on refractive index sensing promise highest sensitivities at smallest area foot-print. Nevertheless, when it comes to large scale fabrication…

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★ 1 cited

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

Convolutional Neural Networks for the segmentation of microcalcification in Mammography Imaging

Gabriele Valvano, Gianmarco Santini, Nicola Martini +4

Cluster of microcalcifications can be an early sign of breast cancer. In this paper we propose a novel approach based on convolutional neural networks for the detection and segment…

cs.CV2018★ 18 cited

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…