As a new interdisciplinary research area, “image-based geometric modeling and mesh generation” integrates image processing, geometric modeling and mesh generation with finite element method (FEM) to solve problems in computational biomedicine, materials sciences and engineering. It is well known that FEM is currently well-developed and efficient, but mesh generation for complex geometries (e.g., the human body) still takes about 80% of the total analysis time and is the major obstacle to reduce the total computation time. It is mainly because none of the traditional approaches is sufficient to effectively construct finite element meshes for arbitrarily complicated domains, and generally a great deal of manual interaction is involved in mesh generation. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion, quality improvement, mesh warping, heterogeneous materials, biomodelcular modeling and simulation, as well as medical and engineering applications.

Cutting-Edge Techniques to Better Analyze and Predict Complex Physical Phenomena Geometric Modeling and Mesh Generation from Scanned Images shows how to integrate image processing, geometric modeling, and mesh generation with the finite element method (FEM) to solve problems in computational biology, medicine, materials science, and engineering. Based on the author’s recent research and course at Carnegie Mellon University, the text explains the fundamentals of medical imaging, image processing, computational geometry, mesh generation, visualization, and finite element analysis. It also explores novel and advanced applications in computational biology, medicine, materials science, and other engineering areas. One of the first to cover this emerging interdisciplinary field, the book addresses biomedical/material imaging, image processing, geometric modeling and visualization, FEM, and biomedical and engineering applications. It introduces image-mesh-simulation pipelines, reviews numerical methods used in various modules of the pipelines, and discusses several scanning techniques, including ones to probe polycrystalline materials. The book next presents the fundamentals of geometric modeling and computer graphics, geometric objects and transformations, and curves and surfaces as well as two isocontouring methods: marching cubes and dual contouring. It then describes various triangular/tetrahedral and quadrilateral/hexahedral mesh generation techniques. The book also discusses volumetric T-spline modeling for isogeometric analysis (IGA) and introduces some new developments of FEM in recent years with applications.

Cutting-Edge Techniques to Better Analyze and Predict Complex Physical Phenomena Geometric Modeling and Mesh Generation from Scanned Images shows how to integrate image processing, geometric modeling, and mesh generation with the finite element method (FEM) to solve problems in computational biology, medicine, materials science, and engineering. Based on the author’s recent research and course at Carnegie Mellon University, the text explains the fundamentals of medical imaging, image processing, computational geometry, mesh generation, visualization, and finite element analysis. It also explores novel and advanced applications in computational biology, medicine, materials science, and other engineering areas. One of the first to cover this emerging interdisciplinary field, the book addresses biomedical/material imaging, image processing, geometric modeling and visualization, FEM, and biomedical and engineering applications. It introduces image-mesh-simulation pipelines, reviews numerical methods used in various modules of the pipelines, and discusses several scanning techniques, including ones to probe polycrystalline materials. The book next presents the fundamentals of geometric modeling and computer graphics, geometric objects and transformations, and curves and surfaces as well as two isocontouring methods: marching cubes and dual contouring. It then describes various triangular/tetrahedral and quadrilateral/hexahedral mesh generation techniques. The book also discusses volumetric T-spline modeling for isogeometric analysis (IGA) and introduces some new developments of FEM in recent years with applications.

The developments in mesh generation are usually driven by the needs of new applications and/or novel algorithms. The last decade has seen a renewed interest in mesh generation and adaptation by the computational engineering community, due to the challenges introduced by complex industrial problems.Another common challenge is the need to handle complex geometries. Nowadays, it is becoming obvious that geometry should be persistent throughout the whole simulation process. Several methodologies that can carry the geometric information throughout the simulation stage are available, but due to the novelty of these methods, the generation of suitable meshes for these techniques is still the main obstacle for the industrial uptake of this technology.This book will cover different aspects of mesh generation and adaptation, with particular emphasis on cutting-edge mesh generation techniques for advanced discretisation methods and complex geometries.

This book constitutes the refereed proceedings of the International Workshop on Mesh Processing in Medical Image Analysis, MeshMed 2012, held in Nice, France, in October 2012 in conjunction with MICCAI 2012, the 15th International Conference on Medical Image Computing and Computer Assisted Intervention. The book includes 16 submissions, 8 were selected for presentation along with the 3 plenary talks representative of the meshing, and 8 were selected for poster presentations. The papers cover a broad range of topics, including statistical shape analysis and atlas construction, novel meshing approaches, soft tissue simulation, quad dominant meshing and mesh based shape descriptors. The described techniques were applied to a variety of medical data including cortical bones, ear canals, cerebral aneurysms and vascular structures.

The five-volume set LNCS 14073-14077 constitutes the proceedings of the 23rd International Conference on Computational Science, ICCS 2023, held in Prague, Czech Republic, during July 3-5, 2023. The total of 188 full papers and 94 short papers presented in this book set were carefully reviewed and selected from 530 submissions. 54 full and 37 short papers were accepted to the main track; 134 full and 57 short papers were accepted to the workshops/thematic tracks. The theme for 2023, "Computation at the Cutting Edge of Science", highlights the role of Computational Science in assisting multidisciplinary research. This conference was a unique event focusing on recent developments in scalable scientific algorithms, advanced software tools; computational grids; advanced numerical methods; and novel application areas. These innovative novel models, algorithms, and tools drive new science through efficient application in physical systems, computational and systems biology, environmental systems, finance, and others.

This volume collects selected contributions from the “Fourth Tetrahedron Workshop on Grid Generation for Numerical Computations”, which was held in Verbania, Italy in July 2013. The previous editions of this Workshop were hosted by the Weierstrass Institute in Berlin (2005), by INRIA Rocquencourt in Paris (2007), and by Swansea University (2010). This book covers different, though related, aspects of the field: the generation of quality grids for complex three-dimensional geometries; parallel mesh generation algorithms; mesh adaptation, including both theoretical and implementation aspects; grid generation and adaptation on surfaces – all with an interesting mix of numerical analysis, computer science and strongly application-oriented problems.

Computational Anatomy (CA) is an emerging discipline aiming to understand anatomy by utilizing a comprehensive set of mathematical tools. CA focuses on providing precise statistical encodings of anatomy with direct application to a broad range of biological and medical settings. During the past two decades, there has been an ever-increasing pace in the development of neuroimaging techniques, delivering in vivo information on the anatomy and physiological signals of different human organs through a variety of imaging modalities such as MRI, x-ray, CT, and PET. These multi-modality medical images provide valuable data for accurate interpretation and estimation of various biological parameters such as anatomical labels, disease types, cognitive states, functional connectivity between distinct anatomical regions, as well as activation responses to specific stimuli. In the era of big neuroimaging data, Bayes’ theorem provides a powerful tool to deliver statistical conclusions by combining the current information and prior experience. When sufficiently good data is available, Bayes’ theorem can utilize it fully and provide statistical inferences/estimations with the least error rate. Bayes’ theorem arose roughly three hundred years ago and has seen extensive application in many fields of science and technology, including recent neuroimaging, ever since. The last fifteen years have seen a great deal of success in the application of Bayes’ theorem to the field of CA and neuroimaging. That said, given that the power and success of Bayes’ rule largely depends on the validity of its probabilistic inputs, it is still a challenge to perform Bayesian estimation and inference on the typically noisy neuroimaging data of the real world. We assembled contributions focusing on recent developments in CA and neuroimaging through Bayesian estimation and inference, in terms of both methodologies and applications. It is anticipated that the articles in this Research Topic will provide a greater insight into the field of Bayesian imaging analysis.

Computational fluid-structure interaction (FSI) and flow simulation are challenging research areas that bring solution and analysis to many classes of problems in science, engineering, and technology. Young investigators under the age of 40 are conducting much of the frontier research in these areas, some of which is highlighted in this volume. The first author of each chapter took the lead role in carrying out the research presented. Some of the topics explored include Direct flow simulation of objects represented by point clouds Computational investigation of leaflet flutter in thinner biological heart valve tissues High-fidelity simulation of hydrokinetic energy applications High-resolution isogeometric analysis of car and tire aerodynamics Computational analysis of air-blast-structure interaction Heart valve computational flow analysis with boundary layer and leaflet contact representation Computational thermal multi-phase flow for metal additive manufacturing This volume will be a valuable resource for early-career researchers and students — not only those interested in computational FSI and flow simulation, but also other fields of engineering and science, including fluid mechanics, solid mechanics, and computational mathematics – as it will provide them with inspiration and guidance for conducting their own successful research. It will also be of interest to senior researchers looking to learn more about successful research led by those under 40 and possibly offer collaboration to these researchers.

This book aims to present dominant applications and use cases of the fast-evolving DT and determines vital Industry 4.0 technologies for building DT that can provide solutions for fighting local and globalmedical emergencies during pandemics. Moreover, it discusses a new framework integrating DT and blockchain technology to provide a more efficient and effective preventive conservation in different applications.