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SAR Prediction and SAR Management for Parallel Transmit MRI
Parallel transmission enables control of the RF field in high-field Magnetic Resonance Imaging (MRI). However, the approach has also caused concerns about the specific absorption rate (SAR) in the patient body. The present work provides new concepts for SAR prediction. A novel approach for generating human body models is proposed, based on a water-fat separated MRI pre-scan. Furthermore, this work explores various approaches for SAR reduction.
Pattern Recognition
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Breast Imaging
This book constitutes the refereed proceedings of the 12th International Workshop on Breast Imaging, IWDM 2014, held in Gifu City, Japan, in June/July 2014. The 24 revised full papers and 73 revised poster papers presented together with 6 invited talks were carefully reviewed and selected from 122 submissions. The papers are organized in topical sections on screening outcomes, ultrasound, breast density, imaging physics, CAD, tomosynthesis and ICT and image processing.
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.
Personalized Multi-Scale Modeling of the Atria: Heterogeneities, Fiber Architecture, Hemodialysis and Ablation Therapy
This book targets three fields of computational multi-scale cardiac modeling. First, advanced models of the cellular atrial electrophysiology and fiber orientation are introduced. Second, novel methods to create patient-specific models of the atria are described. Third, applications of personalized models in basic research and clinical practice are presented. The results mark an important step towards the patient-specific model-based atrial fibrillation diagnosis, understanding and treatment.
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.
Multiscale Modeling of Cardiac Electrophysiology: Adaptation to Atrial and Ventricular Rhythm Disorders and Pharmacological Treatment
Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface.AbstractEnglisch = Multiscale modeling of cardiac electrophysiology helps to better understand the underlying mechanisms of atrial fibrillation, acute cardiac ischemia and pharmacological treatment. For this purpose, measurement data reflecting these conditions have to be integrated into models of cardiac electrophysiology. Several methods for this model adaptation are introduced in this thesis. The resulting effects are investigated in multiscale simulations ranging from the ion channel up to the body surface.
ECG Based Analysis of the Ventricular Repolarisation in the Human Heart
ECG recordings provide diagnostic relevant information on the de- and repolarisation sequences of the heart. A modification of the repolarisation sequence is assumed to cause Torsades de Pointes. Especially drug induced effects on the repolarisation processes are in focus, since some non-cardiac drugs have been associated with sudden cardiac death in the 1990s.The analysis of the ventricular repolarisation using a set of parameters depicting the morphology of the T-wave is introduced in this work. Therefore, new methods of fully automatic patient-specific QRS detection, beat classification and precise T-wave delineation are presented. Using these methods, medical studies are investigated regarding the modification of the T-wave by different compounds. Also the impact of the heart rate on the morphology of the T-wave is part of this research.The reliable identification of ventricular ectopic beats allows an analysis of the influence of these beats on subsequent heart beats. It turned out that the morphology of subsequent heart beats can significantly be changed. This might give new information on the proarrythmical risk of ventricular ectopic beats.
