COCHET , Hubert

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...

BACKGROUND Markers of left atrial (LA) shape may improve the prediction of postablation outcomes in atrial fibrillation (AF). Correlations to LA volume and AF persistence limit their incremental value over current clinical predictors. OBJECTIVE To develop a shape score independent from AF persistence and LA volume using shape-based statistics,...

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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 challenge of non-invasive Electrocardiographic Imaging (ECGI) is to recreate the electrical activity of the heart using body surface potentials. Specifically, there are numerical difficulties due to the ill-posed nature of the problem. We propose a novel method based on Conditional Variational Autoencoders using Deep generative Neural...

Research into artificial intelligence (AI) has made tremendous progress over the past decade. In particular, the AI-powered analysis of images and signals has reached human-level performance in many applications owing to the efficiency of modern machine learning methods, in particular deep learning using convolutional neural networks. Research...

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...

The short-axis view defined such that a series of slices are perpendicular to the long-axis of the left ventricle (LV) is one of the most important views in cardiovascular imaging. Raw trans-axial Computed Tomography (CT) images must be often reformatted prior to diagnostic interpretation in short-axis view. The clinical importance of this...

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...

There has been a recent growing interest for cardiac computed tomography (CT) imaging in the electrophysiological community. This imaging modality indeed allows to locate and assess post-infarct scar heterogeneity, allowing to predict zones of abnormal electrical activity and even personalise EP models. To this end, most of the literature uses...

Non-invasive prediction of optimal targets for efficient radio-frequency ablation is a major challenge in the treatment of ventricular tachycardia.Most of the related modelling work relies on magnetic resonance imaging of the heart for patient-specific personalized electrophysiology simulations.In this study, we used high-resolution computed...

Atrial fibrillation (AF) is a complex cardiac disease impact-ing an ever-growing population and increases 6-fold the risk of thrombusformation. However, image based bio-markers to predict thrombosis inpresence of AF are not well known. This lack of knowledge comes fromthe difficulty to analyse and compare the shape of the Left Atrium (LA)as...

Goal: We present a model-based feature augmentation scheme to improve the performance of a learning algorithm for the detection of cardiac radio-frequency ablation (RFA) targets with respect to learning from images alone. Methods: Initially, we compute image features from delayed-enhanced MRI (DE-MRI) to describe local tissue heterogeneities...

Many uncertainties remain about the relation between post-infarct scars and ventricular arrhythmia. Most post-infarct patients suffer scar-related arrhythmia several years after the infarct event suggesting that scar remodeling is a process that might require years until the affected tissue becomes arrhythmogenic. In clinical practice, a simple...

BACKGROUNDElectrophysiological mapping of ventricular tachycardia (VT) is tedious and poorly reproducible. Substrate analysis on imaging cannot explicitly display VT circuits. OBJECTIVESThis study sought to introduce a computed tomography-based model personalization approach, allowing for the simulation of postinfarction VT in a clinically...

Aims Clinical application of patient-specific cardiac computer models requires fast and robust processing pipelines that can be seamlessly integrated into clinical workflows. We aim at building such a pipeline from computed tomography (CT) images to personalised cardiac electrophysiology (EP) model. The simulation output could be useful in the...

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...

Radiological imaging offers effective measurement of anatomy, which is useful in disease diagnosis and assessment. Previous study has shown that the left atrial wall remodeling can provide information to predict treatment outcome in atrial fibrillation. Nevertheless, the segmentation of the left atrial structures from medical images is still...

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...

Image Integration-Guided VT Ablation. Background: Although multi-detector computed tomog-raphy (MDCT) and cardiac magnetic resonance (CMR) can assess the structural substrate of ventricular tachycardia (VT) in ischemic cardiomyopathy (ICM), non-ICM (NICM), and arrhythmogenic right ventric-ular cardiomyopathy (ARVC), the usefulness of systematic...

Structural changes to the wall of the left atrium are known to occur with conditions that predispose to Atrial fibrillation. Imaging studies have demonstrated that these changes may be detected non-invasively. An important indicator of this structural change is the wall's thickness. Present studies have commonly measured the wall thickness at...