activity
20222026
collaborators

5 papers

cs.CV2026

CardioMOD-Net: A Modal Decomposition-Neural Network Framework for Diagnosis and Prognosis of HFpEF from Echocardiography Cine Loops

Andrés Bell-Navas, Jesús Garicano-Mena, Antonella Ausiello +3

Introduction: Heart failure with preserved ejection fraction (HFpEF) arises from diverse comorbidities and progresses through prolonged subclinical stages, making early diagnosis a…

eess.IV2024

EigenHearts: Cardiac Diseases Classification Using EigenFaces Approach

Nourelhouda Groun, Maria Villalba-Orero, Lucia Casado-Martin +4

In the realm of cardiovascular medicine, medical imaging plays a crucial role in accurately classifying cardiac diseases and making precise diagnoses. However, the field faces sign…

eess.IV2024

A Novel Data Augmentation Tool for Enhancing Machine Learning Classification: A New Application of the Higher Order Dynamic Mode Decomposition for Improved Cardiac Disease Identification

Nourelhouda Groun, Maria Villalba-Orero, Lucia Casado-Martin +4

In this work, a data-driven, modal decomposition method, the higher order dynamic mode decomposition (HODMD), is combined with a convolutional neural network (CNN) in order to impr…

eess.IV2024

Automatic Cardiac Pathology Recognition in Echocardiography Images Using Higher Order Dynamic Mode Decomposition and a Vision Transformer for Small Datasets

Andrés Bell-Navas, Nourelhouda Groun, María Villalba-Orero +3

Heart diseases are the main international cause of human defunction. According to the WHO, nearly 18 million people decease each year because of heart diseases. Also considering th…

eess.IV2022

A Novel Data-Driven Method for the Analysis and Reconstruction of Cardiac Cine MRI

Nourelhouda Groun, Maria Villalba-Orero, Enrique Lara-Pezzi +3

Cardiac cine magnetic resonance imaging (MRI) can be considered the optimal criterion for measuring cardiac function. This imaging technique can provide us with detailed informatio…