85 citations · 200 across the 17 of their papers we have counts for
5 papers · 1 filter
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…
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…
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…
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…
Volumetric parcellation of the right ventricle for regional geometric and functional assessment
Gabriel Bernardino, Amir Hodzic, Helene Langet +5
3D echocardiography is an increasingly popular tool for assessing cardiac remodelling in the right ventricle (RV). It allows quantification of the cardiac chambers without any geom…