152 citations · 248 across the 8 of their papers we have counts for
4 papers · 1 filter
Detection, growth quantification and malignancy prediction of pulmonary nodules using deep convolutional networks in follow-up CT scans
Xavier Rafael-Palou, Anton Aubanell, Mario Ceresa +3
We address the problem of supporting radiologists in the longitudinal management of lung cancer. Therefore, we proposed a deep learning pipeline, composed of four stages that compl…
Pulmonary Nodule Malignancy Classification Using its Temporal Evolution with Two-Stream 3D Convolutional Neural Networks
Xavier Rafael-Palou, Anton Aubanell, Ilaria Bonavita +4
Nodule malignancy assessment is a complex, time-consuming and error-prone task. Current clinical practice requires measuring changes in size and density of the nodule at different…
Re-Identification and Growth Detection of Pulmonary Nodules without Image Registration Using 3D Siamese Neural Networks
Xavier Rafael-Palou, Anton Aubanell, Ilaria Bonavita +4
Lung cancer follow-up is a complex, error prone, and time consuming task for clinical radiologists. Several lung CT scan images taken at different time points of a given patient ne…
Integration of Convolutional Neural Networks for Pulmonary Nodule Malignancy Assessment in a Lung Cancer Classification Pipeline
Ilaria Bonavita, Xavier Rafael-Palou, Mario Ceresa +3
The early identification of malignant pulmonary nodules is critical for better lung cancer prognosis and less invasive chemo or radio therapies. Nodule malignancy assessment done b…