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Multiscale Cohort Modeling of Atrial Electrophysiology : Risk Stratification for Atrial Fibrillation through Machine Learning on Electrocardiograms
An early detection and diagnosis of atrial fibrillation sets the course for timely intervention to prevent potentially occurring comorbidities. Electrocardiogram data resulting from electrophysiological cohort modeling and simulation can be a valuable data resource for improving automated atrial fibrillation risk stratification with machine learning techniques and thus, reduces the risk of stroke in affected patients.
Modeling Human Atrial Patho-Electrophysiology from Ion Channels to ECG - Substrates, Pharmacology, Vulnerability, and P-Waves
Half of the patients suffering from atrial fibrillation (AF) cannot be treated adequately, today. This book presents multi-scale computational methods to advance our understanding of patho-mechanisms, to improve the diagnosis of patients harboring an arrhythmogenic substrate, and to tailor therapy. The modeling pipeline ranges from ion channels on the subcellular level up to the ECG on the body surface. The tailored therapeutic approaches carry the potential to reduce the burden of AF.
A Multiscale In Silico Study to Characterize the Atrial Electrical Activity of Patients With Atrial Fibrillation : A Translational Study to Guide Ablation Therapy
The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.
Magnetic Resonance Imaging on Patients with Implanted Cardiac Pacemakers
The aim of this work was to identify the patterns that can induce heating around implanted cardiac pacemakers during MRI and to develop strategies to counteract them. Two approaches were taken: computer simulations of the occurring electromagnetic field distributions and in-vitro experiments using phantoms in real MRI devices, both for conventional bore-hole and new open MRI systems. Using the open MRI, the observed heating could be reduced significantly.
Solving the Inverse Problem of Electrocardiography in a Realistic Environment
Heart disease is a leading cause of death worldwide. Straightforward information about the cardiac electrophysiology can help to improve the quality of diagnosis of heart diseases. The inverse problem of electrocardiography and the intracardiac catheter measurement are two ways to get access to the electrophysiology in the heart. In this thesis six research topics related to these two techniques are included.
Surgery Simulation and Soft Tissue Modeling
This book constitutes the refereed proceedings of the International Symposium on Surgery Simulation and Soft Tissue Modeling, IS4TM 2003, held in Juan-Les-Pins, France in June 2003. The 33 revised full papers presented together with 3 invited papers were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on soft tissue models, haptic rendering, cardiac modeling, and patient specific simulators.
Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2012
The three-volume set LNCS 7510, 7511, and 7512 constitutes the refereed proceedings of the 15th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2012, held in Nice, France, in October 2012. Based on rigorous peer reviews, the program committee carefully selected 252 revised papers from 781 submissions for presentation in three volumes. The first volume includes 91 papers organized in topical sections on abdominal imaging, computer-assisted interventions and robotics; computer-aided diagnosis and planning; image reconstruction and enhancement; analysis of microscopic and optical images; computer-assisted interventions and robotics; image segmentation; cardiovascular imaging; and brain imaging: structure, function and disease evolution.
Characterizing Cardiac Electrophysiology during Radiofrequency Ablation : An Integrative Ex vivo, In silico, and In vivo Approach
Catheter ablation is a major treatment for atrial tachycardias. Hereby, the precise monitoring of the lesion formation is an important success factor. This book presents computational, wet-lab, and clinical studies with the aim of evaluating the signal characteristics of the intracardiac electrograms (IEGMs) recorded around ablation lesions from different perspectives. The detailed analysis of the IEGMs can optimize the description of durable and complex lesions during the ablation procedure.
XII Mediterranean Conference on Medical and Biological Engineering and Computing 2010
Over the past three decades, the exploding number of new technologies and applications introduced in medical practice, often powered by advances in biosignal processing and biomedical imaging, created an amazing account of new possibilities for diagnosis and therapy, but also raised major questions of appropriateness and safety. The accelerated development in this field, alongside with the promotion of electronic health care solutions, is often on the basis of an uncontrolled diffusion and use of medical technology. The emergence and use of medical devices is multiplied rapidly and today there exist more than one million different products available on the world market. Despite the fact that the rising cost of health care, partly resulting from the new emerging technological applications, forms the most serious and urgent problem for many governments today, another important concern is that of patient safety and user protection, issues that should never be compromised and expelled from the Biomedical Engineering research practice agenda.
