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Группа авторов. Computational Modeling and Simulation Examples in Bioengineering
Table of Contents
List of Tables
List of Illustrations
Guide
Pages
Computational Modeling and Simulation Examples in Bioengineering
Editor Biography
Author Biographies
Preface
1 Computational Modeling of Abdominal Aortic Aneurysms
1.1 Background
1.2 Clinical Trials for AAA
1.3 Computational Methods Applied for AAA
1.4 Experimental Testing to Determine Material Properties
1.5 Material Properties of the Aorta Wall
1.6 ILT Modeling
1.7 Finite Element Procedure and Fluid–Structure Interaction
1.7.1 Displacement Force Calculations
1.7.2 Shear Stress Calculation
1.7.3 Modeling the Deformation of Blood Vessels
1.7.4 FSI Interaction
1.8 Data Mining and Future Clinical Decision Support System
1.9 Conclusions
Exercise 1.1 Modeling of Blood Flow Within the AAA
Generation of the Finite Element Model
Boundary Conditions
Results
Modeling of AAA Assuming Rigid Walls
Modeling AAA with Deformable Walls
References
2 Modeling the Motion of Rigid and Deformable Objects in Fluid Flow
2.1 Introduction
2.2 Numerical Model
2.2.1 Modeling Blood Flow
2.2.2 Modeling Solid–Fluid Interaction
2.2.2.1 Modeling the Motion of Rigid Particle
2.2.2.2 Modeling the Motion of Deformable Particle
2.2.3 Modeling Deformation of the Particle
2.2.3.1 Force Caused by the Surface Strain of Membrane
2.2.3.2 Force Caused by the Bending of the Membrane
2.2.3.3 Force Caused by the Change of Surface area of the Membrane
2.2.3.4 Force Caused by the Change of Volume
2.2.4 Modeling the Flow of Two Fluids with Different Viscosity that are Separated by the Membrane of the Solid
2.3 Results
2.3.1 Modeling the Behavior of Particles in Poiseuille Flow
2.3.2 Modeling the Behavior of Particles in Shear Flow
2.3.3 Modeling Behavior of Particles in Stenotic Artery
2.3.4 Modeling Behavior of Particles in Artery with Bifurcation
2.4 Conclusion
References
3 Application of Computational Methods in Dentistry
3.1 Introduction
3.2 Finite Element Method in Dental Research
3.2.1 Development of FEM in Dental Research
3.2.1.1 Morphology and Dimensions of the Structures – Application of Digital Imaging Systems
3.2.1.2 FE Model – Required/Composing Structures
3.2.1.3 Simulating Occlusal Load
3.2.1.4 Boundary Conditions
3.2.1.5 Importance of Periodontal Ligament, Spongious, and Cortical Bone
3.2.2 Overview of FEM in Dental Research – Most Important Topics in the Period 2010–2020
3.2.2.1 FEM in the Research Related to Implants, Restorative Dentistry, and Prosthodontics
3.2.2.2 FEM in Analysis of Biomechanical Behavior of Structures in Masticatory Complex
3.2.2.3 FEM in Orthodontic Research
3.2.2.4 FEM in Studies of Trauma in the Dentoalveolar Region
3.3 Examples of FEA in Clinical Research in Dentistry
3.3.1 Example 1– Assessment of Critical Breaking Force and Failure Index. 3.3.1.1 Background
3.3.1.2 Materials and Methods
3.3.1.2.1 Tooth Preparation
3.3.1.2.2 Imaging of Considered Teeth
3.3.1.2.3 Assessment of the Critical Force
3.3.1.2.4 Development of the Finite Element Models. 3.3.1.2.4.1 Reconstruction of 3D Models
3.3.1.2.4.2 Post‐Processing of Raw 3D Mesh and Generation of “Virtual Models”
3.3.1.2.4.3 Discretization of Three‐Dimensional Meshes and Assignment of Material Characteristics
3.3.1.2.4.4 Definition of Boundary Conditions – Constraints
3.3.1.2.4.5 Finite Element Analysis
3.3.1.2.4.6 Shrinkage Stress
3.3.1.2.4.7 Definition of Boundary Conditions – Loads
3.3.1.3 Results and Discussion
3.3.2 Example 2 – Assessment of the Dentine Fatigue Failure
3.3.2.1 Background
3.3.2.2 Materials and Methods. 3.3.2.2.1 Obtaining Teeth Geometry
3.3.2.2.2 FEM Procedures
3.3.2.2.2.1 Dentin Fatigue Assessment and Residual Lifetime Prediction
3.3.2.3 Results and Discussion
References
4 Determining Young's Modulus of Elasticity of Cortical Bone from CT Scans
4.1 Introduction
4.2 Bone Structure
4.3 Young's Modulus of Elasticity of Bone Tissue. 4.3.1 Factors Influencing Elasticity Modulus
4.3.2 Experimental Calculation of Elasticity Modulus
4.4 Tool for Calculating the Young's Modulus of Elasticity of Cortical Bone from CT Scans. 4.4.1 Theoretical Background
4.4.2 Practical Application
4.5 Numerical Analysis of Femoral Bone Using Calculated Elasticity Modulus. 4.5.1 Femoral Bone Model
4.5.2 Material Properties
4.5.3 Boundary Conditions
4.5.4 Obtained Results
4.5.4.1 Case 1
4.5.4.2 Case 2
4.5.4.3 Case 3
4.5.4.4 Comparison of the Obtained Results
4.6 Conclusion
Acknowledgements
References
5 Parametric Modeling of Blood Flow and Wall Interaction in Aortic Dissection
5.1 Introduction
5.2 Medical Background. 5.2.1 Circulatory System
5.2.2 Aorta
5.2.3 Structure and Function of the Arterial Wall
5.2.4 Aortic Dissection
5.2.5 History of Aortic Dissection
5.2.6 Classification of Aortic Dissection
5.2.7 Diagnostic Techniques
5.2.7.1 Aortography
5.2.7.2 Computed Tomography
5.2.7.3 Echocardiography
5.2.7.4 Magnetic Resonance
5.2.7.5 Intravascular Ultrasound
5.2.8 Treatment of Acute Aortic Dissection
5.2.8.1 Drug Therapy
5.2.8.2 Surgical Treatment
5.3 Theoretical Background
5.3.1 Continuum Mechanics
5.3.1.1 Lagrange and Euler's Formulation of the Material Derivative
5.3.1.2 Law of Conservation of Mass
5.3.1.3 Navier–Stokes Equations
5.3.1.4 Equations of Solid Motion
5.3.2 Solid–Fluid Interaction
5.4 Blood Flow in the Arteries
5.4.1 Stationary Flow
5.4.2 Oscillatory (Pulsating) Flow
5.4.3 Flow in Curved Pipes
5.4.4 Blood Flow in Bifurcations
5.5 Numerical Simulations
5.6 Conclusions
References
6 Application of AR Technology in Bioengineering
6.1 Introduction
6.2 Review of AR Technology
6.2.1 Augmented Reality Devices
6.2.2 AR Screen Based on the Monitor
6.2.3 AR Screen Based on Mobile Devices
6.2.4 Head Mounting Screen
6.2.5 AR in Biomedical Engineering
6.3 Marker‐based AR Simple Application, Based on the OpenCV Framework
6.3.1 Generating ArUco Markers in OpenCV
6.4 Marker‐less AR Simple Application, Based on the OpenCV Framework
6.4.1 Use Feature Descriptors to Find the Target Image in a Video
6.4.2 Calculating the Camera‐intrinsic Matrix
6.4.3 Rendering AR with a Simple OpenGL Object (Cube)
6.5 Conclusion
References
7 Augmented Reality Balance Physiotherapy in HOLOBALANCE Project
7.1 Introduction
7.2 Motivation
7.3 Holograms‐Based Balance Physiotherapy
7.4 Mock‐ups
7.4.1 Meta 2
7.4.2 HoloLens
7.4.3 Holobox
7.4.4 Modeling of BP in Unity 3D
7.5 Final Version
7.5.1 Balance Physiotherapy Hologram (BPH)
7.5.2 BPH–MCWS Communication
7.5.3 Speech Recognition
7.5.4 Localization
7.5.5 Motion Capturing
7.5.6 Marker‐less Motion Capture
7.5.7 Marker‐based Motion Capture
7.5.8 Optical Systems
7.5.9 World Tracking
7.6 Biomechanical Model of Avatar Based on the Muscle Modeling
7.6.1 Muscle Modeling
References
8 Modeling of the Human Heart – Ventricular Activation Sequence and ECG Measurement
8.1 Introduction
8.2 Materials and Methods
8.2.1 Material Model Based on Holzapfel Experiments
8.2.2 Biaxial Loading: Experimental Curves
8.3 Determination of Stretches in the Material Local Coordinate System
8.4 Determination of Normal Stresses from Current Stretches
8.4.1 Determination of Shear Stresses from Current Shear Strains
8.5 Results and Discussion
8.6 Conclusion
Acknowledgements
References
9 Implementation of Medical Image Processing Algorithms on FPGA Using Xilinx System Generator
9.1 Brief Introduction to FPGA
9.1.1 Xilinx System Generator
Algorithm Exploration
Implementing Part of a Larger Design
Implementing a Complete Design
9.1.2 Image Processing on FPGAs Using XSG
9.2 Building a Simple Model Using XSG
9.3 Medical Image Processing Using XSG. 9.3.1 Image Pre‐ and Post‐Processing
9.3.2 Algorithms for Image Preprocessing. 9.3.2.1 Algorithm for Negative Image
9.3.2.2 Algorithm for Image Contrast Stretching
9.3.2.3 Image Edge Detection
9.3.3 Hardware Co‐Simulation
9.4 Results and Discussion
9.5 Conclusions
Acknowledgments
References
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IEEE Press Series in Biomedical Engineering
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