Mass-spring systems are considered the simplest and most intuitive of all deformable models. They are computationally efficient, and can handle large deformations with ease. But they suffer several intrinsic limitations. In this book a modified mass-spring system for physically based deformation modeling that addresses the limitations and solves them elegantly is presented. Several implementations in modeling breast mechanics, heart mechanics and for elastic images registration are presented.
This book constitutes the proceedings of the 13th International Conference on Parallel Computing Technologies, PaCT 2015, held in Petrozavodsk, Russia, during August / September 2015. The 37 full papers and 14 short papers presented were carefully reviewed and selected from 87 submissions. The papers are organized in topical sections on parallel models, algorithms and programming methods; unconventional computing; cellular automata; distributed computing; special processors programming techniques; applications.
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.
In this work, the physiological effects of time-varying magnetic fields up to 100 kHz have been investigated, namely magnetic stimulation and body warming. Simulation studies were based on numerical calculations on sophisticated cell and body models. In addition, magnetic stimulation thresholds have been determined experimentally.The project was carried out within the scope of the development of Magnetic Particle Imaging, a new imaging technology for medical diagnostics.
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.
This work provides methods to measure and analyze features of atrial electrograms - especially complex fractionated atrial electrograms (CFAEs) - mathematically. Automated classification of CFAEs into clinical meaningful classes is applied and the newly gained electrogram information is visualized on patient specific 3D models of the atria. Clinical applications of the presented methods showed that quantitative measures of CFAEs reveal beneficial information about the underlying arrhythmia.
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.