LY , Buntheng

Sudden cardiac death (SCD) is a major health concern responsible for up to a yearly mortality of 400,000 in the US, and a similar figure in Europe. SCD is a consequence of the sudden and total stop of cardiac activity, also known as the sudden cardiac arrest (SCA). A study monitoring the cardiac activity has linked the SCA to ventricular...

We propose a data augmentation method to improve thesegmentation accuracy of the convolutional neural network on multi-modality cardiac magnetic resonance (CMR) dataset. The strategy aims to reduce over-fitting of the network toward any specific intensity or contrast of the training images by introducing diversity in...

International audience

Aims: Electrocardiographic Imaging (ECGI) is a promising tool to map the electrical activity of the heart non-invasively using body surface potentials (BSP). However, it is still challenging due to the mathematically ill-posed nature of the inverse problem to solve. Novel approaches leveraging progress in artificial intelligence could alleviate...

The aim of this study is to create an automatic frameworkfor sustained ventricular arrhythmia (VA) prediction using cardiac com-puted tomography (CT) images. We built an image processing pipelineand a deep learning network to explore the relation between post-infarctleft ventricular myocardium thickness and previous occurrence of VA.Our...

This chapter focuses on how we can best predict the future health of patients, known as prognosis. This encompasses areas such as risk prediction and predicting response to treatment. A clinical opinion piece summarises the role of prognosis in clinical care and highlights the areas where AI has already had an impact in this area. The technical...

Post-infarction scar remodelling may start and evolve at a different pace across patients, often requiring years until the affected tissue becomes arrhythmogenic. Current risk stratification strategies lack sensitivity and specificity, and therefore more knowledge is required (e.g. new biomarkers and insights about the appropriate time point to...

National audience

Purpose: A new deep-learning based method for automatic eye fundus diagnosis using multispectral images is proposed. The method discriminates between healthy and diseased eyes exploiting the potential of multispectral data. Among other pathologies, those mainly considered were age-related macular degeneration (ARMD), glaucoma and diabetic...

Heterogeneity of left ventricular (LV) myocardium infarction scar plays an important role as anatomical substrate in ventricular arrhythmia (VA) mechanism. LV myocardium thinning, as observed on cardiac computed tomography (CT), has been shown to correlate with LV myocardial scar and with abnormal electrical activity. In this project, we...

The tremendous advancement of cardiac imaging methods, the substantial progress in predictive modelling, along with the amount of new investigative multimodalities, challenge the current technologies in the cardiology field. Innovative, robust and multimodal tools need to be created in order to fuse imaging data (e.g., MR, CT) with mapped...