activity
20172020
most citedIntegration of Convolutional Neural Networks for Pulmonary Nodule Malignancy Assessment in a Lung Cancer Classification Pipeline

85 citations · 153 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV202014 cited

Handling confounding variables in statistical shape analysis -- application to cardiac remodelling

Gabriel Bernardino, Oualid Benkarim, María Sanz-de la Garza +7

Statistical shape analysis is a powerful tool to assess organ morphologies and find shape changes associated to a particular disease. However, imbalance in confounding factors, suc…

physics.med-ph202011 cited

A radiomics approach to analyze cardiac alterations in hypertension

Irem Cetin, Steffen E. Petersen, Sandy Napel +3

Hypertension is a medical condition that is well-established as a risk factor for many major diseases. For example, it can cause alterations in the cardiac structure and function o…

eess.IV2020

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…

cs.CV2020

Medical-based Deep Curriculum Learning for Improved Fracture Classification

Amelia Jiménez-Sánchez, Diana Mateus, Sonja Kirchhoff +5

Current deep-learning based methods do not easily integrate to clinical protocols, neither take full advantage of medical knowledge. In this work, we propose and compare several st…

eess.IV2019

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…

eess.IV201985 cited

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…