Widely developed for clinical screening, electrocardiogram (ECG) recordings capture the
cardiac electrical activity from the body surface. ECG analysis can therefore be a crucial first …

The electrocardiogram is the most widely used diagnostic tool that records the electrical
activity of the heart and, therefore, its use for identifying markers for early diagnosis and …

Cardiac in silico clinical trials can virtually assess the safety and efficacy of therapies using
human-based modelling and simulation. These technologies can provide mechanistic …

Aims Patient-to-patient anatomical differences are an important source of variability in the
electrocardiogram, and they may compromise the identification of pathological …

Changes induced by intrauterine growth restriction (IUGR) in cardiovascular anatomy and
function that persist throughout life have been associated with a higher predisposition to …

Reconstructing 3D ventricular surfaces from 2D cardiac MR data is challenging due to the
sparsity of the input data and the presence of interslice misalignment. It is usually formulated …

Due to many new medical uses, the value of ECG classification is very demanding. There
are some Machine Learning (ML) algorithms currently available that can be used for ECG …

Cardiac digital twins are personalized virtual representations used to understand complex
heart mechanisms. Solving the ECG inverse problem is crucial for accurate virtual heart …

Whilst the electrocardiogram (ECG) is an essential tool for diagnosing cardiac electrical
abnormalities, its characteristics are dependent on anatomical variability. Specifically …

Dans cette thèse, nous nous intéressons à la modélisation mathématique de
l'électrophysiologie cardiaque et plus précisément, l'étude numérique de l'activité électrique …