research
∙
08/12/2023
Evaluation of cinematic volume rendering open-source and commercial solutions for the exploration of congenital heart data
Detailed anatomical information is essential to optimize medical decisio...
share
research
∙
07/07/2023
Unsupervised Segmentation of Fetal Brain MRI using Deep Learning Cascaded Registration
Accurate segmentation of fetal brain magnetic resonance images is crucia...
research
∙
10/19/2022
In-silico analysis of the influence of pulmonary vein configuration on left atrial haemodynamics and thrombus formation in a large cohort
Atrial fibrillation (AF) is considered the most common human arrhythmia....
research
∙
10/19/2022
Geometric Deep Learning for the Assessment of Thrombosis Risk in the Left Atrial Appendage
The assessment of left atrial appendage (LAA) thrombogenesis has experie...
research
∙
03/20/2022
Attri-VAE: attribute-based, disentangled and interpretable representations of medical images with variational autoencoders
Deep learning (DL) methods where interpretability is intrinsically consi...
research
∙
11/25/2021
Generalizing electrocardiogram delineation: training convolutional neural networks with synthetic data augmentation
Obtaining per-beat information is a key task in the analysis of cardiac ...
research
∙
10/02/2020
Joint data imputation and mechanistic modelling for simulating heart-brain interactions in incomplete datasets
The use of mechanistic models in clinical studies is limited by the lack...
research
∙
07/21/2020
A radiomics approach to analyze cardiac alterations in hypertension
Hypertension is a medical condition that is well-established as a risk f...
research
∙
05/11/2020
ECG-DelNet: Delineation of Ambulatory Electrocardiograms with Mixed Quality Labeling Using Neural Networks
Electrocardiogram (ECG) detection and delineation are key steps for nume...
research
∙
09/25/2019
A Radiomics Approach to Computer-Aided Diagnosis with Cardiac Cine-MRI
Use expert visualization or conventional clinical indices can lack accur...
research
∙
07/25/2019
Decision Tree Learning for Uncertain Clinical Measurements
Clinical decision requires reasoning in the presence of imperfect data. ...
research
∙
11/16/2018
Fast quasi-conformal regional flattening of the left atrium
Two-dimensional representation of 3D anatomical structures is a simple a...
research
∙
09/20/2018
A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts
Rule-based methods are often used for assigning fiber orientation to car...
research
∙
06/17/2018
