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Patient-specific Hemodynamic Computations: Application to Personalized Diagnosis of Cardiovascular Pathologies
Hemodynamic computations represent a state-of-the-art approach for patient-specific assessment of cardiovascular pathologies. The book presents the development of reduced-order multiscale hemodynamic models for coronary artery disease, aortic coarctation and whole body circulation, which can be applied in routine clinical settings for personalized diagnosis. Specific parameter estimation frameworks are introduced for calibrating the parameters of the models and high performance computing solutions are employed to reduce their execution time. The personalized computational models are validated against patient-specific measurements. The book is written for scientists in the field of biomedical engineering focusing on the cardiovascular system, as well as for research-oriented physicians in cardiology and industrial players in the field of healthcare technologies.
Artificial Intelligence for Computational Modeling of the Heart
Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient's heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation
Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges
This book constitutes the thoroughly refereed post-workshop proceedings of the 10th International Workshop on Statistical Atlases and Computational Models of the Heart: Atrial Segmentation and LV Quantification Challenges, STACOM 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 42 revised full workshop papers were carefully reviewed and selected from 76 submissions. The topics of the workshop included: cardiac imaging and image processing, machine learning applied to cardiac imaging and image analysis, atlas construction, statistical modelling of cardiac function across different patient populations, cardiac computational physiology, model customization, atlas based functional analysis, ontological schemata for data and results, integrated functional and structural analyses, as well as the pre-clinical and clinical applicability of these methods.
Mimpi Selalu Indah
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2020 24th International Conference on System Theory, Control and Computing (ICSTCC)
The Joint Conference is for the seventh time organized in this format The main goal of this conference is to provide a multidisciplinary forum between researchers from industry and academia to discuss state of the art topics in system theory, control and computing, and to present recent research results and prospects for development in this evolving area
Simulating Complex Systems by Cellular Automata
Deeply rooted in fundamental research in Mathematics and Computer Science, Cellular Automata (CA) are recognized as an intuitive modeling paradigm for Complex Systems. Already very basic CA, with extremely simple micro dynamics such as the Game of Life, show an almost endless display of complex emergent behavior. Conversely, CA can also be designed to produce a desired emergent behavior, using either theoretical methodologies or evolutionary techniques. Meanwhile, beyond the original realm of applications - Physics, Computer Science, and Mathematics – CA have also become work horses in very different disciplines such as epidemiology, immunology, sociology, and finance. In this context of f...
