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E-raamat: Computational Modeling and Simulation Examples in Bioengineering

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A systematic overview of the quickly developing field of bioengineeringwith state-of-the-art modeling software! Computational Modeling and Simulation Examples in Bioengineering provides a comprehensive introduction to the emerging field of bioengineering. It provides the theoretical background necessary to simulating pathological conditions in the bones, muscles, cardiovascular tissue, and cancers, as well as lung and vertigo disease. The methodological approaches used for simulations include the finite element, dissipative particle dynamics, and lattice Boltzman. The text includes access to a state-of-the-art software package for simulating the theoretical problems. In this way, the book enhances the reader's learning capabilities in the field of biomedical engineering.

The aim of this book is to provide concrete examples of applied modeling in biomedical engineering. Examples in a wide range of areas equip the reader with a foundation of knowledge regarding which problems can be modeled with which numerical methods. With more practical examples and more online software support than any competing text, this book organizes the field of computational bioengineering into an accessible and thorough introduction. Computational Modeling and Simulation Examples in Bioengineering:





Includes a state-of-the-art software package enabling readers to engage in hands-on modeling of the examples in the book Provides a background on continuum and discrete modeling, along with equations and derivations for three key numerical methods Considers examples in the modeling of bones, skeletal muscles, cartilage, tissue engineering, blood flow, plaque, and more Explores stent deployment modeling as well as stent design and optimization techniques Generates different examples of fracture fixation with respect to the advantages in medical practice applications

Computational Modeling and Simulation Examples in Bioengineering is an excellent textbook for students of bioengineering, as well as a support for basic and clinical research. Medical doctors and other clinical professionals will also benefit from this resource and guide to the latest modeling techniques.
Editor Biography xi
Author Biographies xii
Preface xv
1 Computational Modeling of Abdominal Aortic Aneurysms
1(32)
Nenad D. Filipovic
1.1 Background
1(1)
1.2 Clinical Trials for AAA
2(1)
1.3 Computational Methods Applied for AAA
3(3)
1.4 Experimental Testing to Determine Material Properties
6(2)
1.5 Material Properties of the Aorta Wall
8(1)
1.6 ILT Modeling
9(3)
1.7 Finite Element Procedure and Fluid-Structure Interaction
12(4)
1.7.1 Displacement Force Calculations
12(1)
1.7.2 Shear Stress Calculation
13(1)
1.7.3 Modeling the Deformation of Blood Vessels
13(2)
1.7.4 FSI Interaction
15(1)
1.8 Data Mining and Future Clinical Decision Support System
16(3)
1.9 Conclusions
19(14)
References
23(10)
2 Modeling the Motion of Rigid and Deformable Objects in Fluid Flow
33(54)
Tijana Djukic
Nenad D. Filipovic
2.1 Introduction
33(2)
2.2 Numerical Model
35(19)
2.2.1 Modeling Blood Flow
36(4)
2.2.2 Modeling Solid-Fluid Interaction
40(2)
2.2.2.1 Modeling the Motion of Rigid Particle
42(3)
2.2.2.2 Modeling the Motion of Deformable Particle
45(1)
2.2.3 Modeling Deformation of the Particle
46(1)
2.2.3.1 Force Caused by the Surface Strain of Membrane
47(4)
2.2.3.2 Force Caused by the Bending of the Membrane
51(1)
2.2.3.3 Force Caused by the Change of Surface area of the Membrane
51(1)
2.2.3.4 Force Caused by the Change of Volume
52(1)
2.2.4 Modeling the Flow of Two Fluids with Different Viscosity that are Separated by the Membrane of the Solid
52(2)
2.3 Results
54(27)
2.3.1 Modeling the Behavior of Particles in Poiseuille Flow
55(2)
2.3.2 Modeling the Behavior of Particles in Shear Flow
57(17)
2.3.3 Modeling Behavior of Particles in Stenotic Artery
74(3)
2.3.4 Modeling Behavior of Particles in Artery with Bifurcation
77(4)
2.4 Conclusion
81(6)
References
82(5)
3 Application of Computational Methods in Dentistry
87(54)
Ksenija Zelic Mihajtovic
Arso M. Vukicevic
Nenad D. Filipovic
3.1 Introduction
87(1)
3.2 Finite Element Method in Dental Research
88(15)
3.2.1 Development of FEM in Dental Research
89(1)
3.2.1.1 Morphology and Dimensions of the Structures - Application of Digital Imaging Systems
90(1)
3.2.1.2 FE Model - Required/Composing Structures
91(1)
3.2.1.3 Simulating Occlusal Load
92(2)
3.2.1.4 Boundary Conditions
94(1)
3.2.1.5 Importance of Periodontal Ligament, Spongious, and Cortical Bone
95(1)
3.2.2 Overview of FEM in Dental Research - Most Important Topics in the Period 2010-2020
96(1)
3.2.2.1 FEM in the Research Related to Implants, Restorative Dentistry, and Prosthodontics
97(4)
3.2.2.2 FEM in Analysis of Biomechanical Behavior of Structures in Masticatory Complex
101(1)
3.2.2.3 FEM in Orthodontic Research
102(1)
3.2.2.4 FEM in Studies of Trauma in the Dentoalveolar Region
103(1)
3.3 Examples of FEA in Clinical Research in Dentistry
103(38)
3.3.1 Example 1 - Assessment of Critical Breaking Force and Failure Index
104(1)
3.3.1.1 Background
104(1)
3.3.1.2 Materials and Methods
104(7)
3.3.1.3 Results and Discussion
111(7)
3.3.2 Example 2 - Assessment of the Dentine Fatigue Failure
118(1)
3.3.2.1 Background
118(1)
3.3.2.2 Materials and Methods
119(5)
3.3.2.3 Results and Discussion
124(7)
References
131(10)
4 Determining Young's Modulus of Elasticity of Cortical Bone from CT Scans
141(34)
Aleksandra Vulovic
Nenad D. Filipovic
4.1 Introduction
141(2)
4.2 Bone Structure
143(2)
4.3 Young's Modulus of Elasticity of Bone Tissue
145(6)
4.3.1 Factors Influencing Elasticity Modulus
145(1)
4.3.2 Experimental Calculation of Elasticity Modulus
146(5)
4.4 Tool for Calculating the Young's Modulus of Elasticity of Cortical Bone from CT Scans
151(6)
4.4.1 Theoretical Background
151(1)
4.4.2 Practical Application
152(5)
4.5 Numerical Analysis of Femoral Bone Using Calculated Elasticity Modulus
157(12)
4.5.1 Femoral Bone Model
157(2)
4.5.2 Material Properties
159(1)
4.5.3 Boundary Conditions
159(2)
4.5.4 Obtained Results
161(4)
4.5.4.1 Case 1
165(1)
4.5.4.2 Case 2
165(1)
4.5.4.3 Case 3
166(1)
4.5.4.4 Comparison of the Obtained Results
166(3)
4.6 Conclusion
169(6)
Acknowledgements
169(1)
References
170(5)
5 Parametric Modeling of Blood Flow and Wall Interaction in Aortic Dissection
175(44)
Igor B. Saveljic
Nenad D. Filipovic
5.1 Introduction
175(2)
5.2 Medical Background
177(12)
5.2.1 Circulatory System
177(1)
5.2.2 Aorta
178(1)
5.2.3 Structure and Function of the Arterial Wall
179(2)
5.2.4 Aortic Dissection
181(1)
5.2.5 History of Aortic Dissection
182(1)
5.2.6 Classification of Aortic Dissection
182(3)
5.2.7 Diagnostic Techniques
185(1)
5.2.7.1 Aortography
185(1)
5.2.7.2 Computed Tomography
185(1)
5.2.7.3 Echocardiography
186(1)
5.2.1 A Magnetic Resonance
186(1)
5.2.7.5 Intravascular Ultrasound
187(1)
5.2.8 Treatment of Acute Aortic Dissection
187(1)
5.2.8.1 Drug Therapy
187(1)
5.2.8.2 Surgical Treatment
188(1)
5.3 Theoretical Background
189(7)
5.3.1 Continuum Mechanics
189(1)
5.3.1.1 Lagrange and Euler's Formulation of the Material Derivative
189(2)
5.3.1.2 Law of Conservation of Mass
191(1)
5.3.1.3 Navier-Stokes Equations
192(1)
5.3.1.4 Equations of Solid Motion
193(3)
5.3.2 Solid-Fluid Interaction
196(1)
5.4 Blood Flow in the Arteries
196(5)
5.4.1 Stationary Flow
197(1)
5.4.2 Oscillatory (Pulsating) Flow
198(1)
5.4.3 Flow in Curved Pipes
199(1)
5.4.4 Blood Flow in Bifurcations
200(1)
5.5 Numerical Simulations
201(12)
5.6 Conclusions
213(6)
References
213(6)
6 Application of AR Technology in Bioengineering
219(40)
Dalibor D. Nikolic
Nenad D. Filipovic
6.1 Introduction
219(1)
6.2 Review of AR Technology
220(7)
6.2.1 Augmented Reality Devices
220(1)
6.2.2 AR Screen Based on the Monitor
221(1)
6.2.3 AR Screen Based on Mobile Devices
221(1)
6.2.4 Head Mounting Screen
221(3)
6.2.5 AR in Biomedical Engineering
224(3)
6.3 Marker-based AR Simple Application, Based on the OpenCV Framework
227(8)
6.3.1 Generating ArUco Markers in OpenCV
229(6)
6.4 Marker-less AR Simple Application, Based on the OpenCV Framework
235(20)
6.4.1 Use Feature Descriptors to Find the Target Image in a Video
236(11)
6.4.2 Calculating the Camera-intrinsic Matrix
247(3)
6.4.3 Rendering AR with a Simple OpenGL Object (Cube)
250(5)
6.5 Conclusion
255(4)
References
255(4)
7 Augmented Reality Balance Physiotherapy in HOLOBALANCE Project
259(46)
Nenad D. Filipovic
Zarko Milosevic
7.1 Introduction
259(2)
7.2 Motivation
261(4)
7.3 Holograms-Based Balance Physiotherapy
265(1)
7.4 Mock-ups
265(8)
7.4.1 Meta 2
266(2)
7.4.2 Holo Lens
268(2)
7.4.3 Holobox
270(2)
7.4.4 Modeling of BP in Unity 3D
272(1)
7.5 Final Version
273(22)
7.5.1 Balance Physiotherapy Hologram (BPH)
278(1)
7.5.2 BPH-MCWS Communication
279(7)
7.5.3 Speech Recognition
286(2)
7.5.4 Localization
288(1)
7.5.5 Motion Capturing
288(1)
7.5.6 Marker-less Motion Capture
289(1)
7.5.7 Marker-based Motion Capture
290(1)
7.5.8 Optical Systems
291(1)
7.5.9 World Tracking
291(4)
7.6 Biomechanical Model of Avatar Based on the Muscle Modeling
295(10)
7.6.1 Muscle Modeling
298(3)
References
301(4)
8 Modeling of the Human Heart - Ventricular Activation Sequence and ECG Measurement
305(18)
Nenad D. Filipovic
8.1 Introduction
305(2)
8.2 Materials and Methods
307(3)
8.2.1 Material Model Based on Holzapfel Experiments
309(1)
8.2.2 Biaxial Loading: Experimental Curves
309(1)
8.3 Determination of Stretches in the Material Local Coordinate System
310(3)
8.4 Determination of Normal Stresses from Current Stretches
313(3)
8.4.1 Determination of Shear Stresses from Current Shear Strains
314(2)
8.5 Results and Discussion
316(1)
8.6 Conclusion
317(6)
Acknowledgements
320(1)
References
320(3)
9 Implementation of Medical Image Processing Algorithms on FPGA Using Xilinx System Generator
323(36)
Tijana I. SuStersiC
Nenad D. Filipovic
9.1 Brief Introduction to FPGA
323(6)
9.1.1 Xilinx System Generator
325(1)
Algorithm Exploration
326(1)
Implementing Part of a Larger Design
327(1)
Implementing a Complete Design
327(1)
9.1.2 Image Processing on FPGAs Using XSG
327(2)
9.2 Building a Simple Model Using XSG
329(5)
Prerequisites
330(4)
9.3 Medical Image Processing Using XSG
334(18)
9.3.1 Image Pre- and Post-Processing
334(1)
9.3.2 Algorithms for Image Preprocessing
335(1)
9.3.2.1 Algorithm for Negative Image
335(2)
9.3.2.2 Algorithm for Image Contrast Stretching
337(1)
9.3.2.3 Image Edge Detection
337(14)
9.3.3 Hardware Co-Simulation
351(1)
9.4 Results and Discussion
352(7)
9.5 Conclusions
359(1)
Acknowledgments 359(1)
References 360(3)
Index 363
NENAD D. FILIPOVIC, PhD, is a Professor in the Faculty of Engineering and Head of the Center for Bioengineering at the University of Kragujevac, Serbia. He also leads national and international projects in bioengineering and software development, including joint research projects with Harvard University and the University of Texas. He is a Managing Editor for the Journal of the Serbian Society for Computational Mechanics and a member of IEEE, European Society of Biomechanics (ESB).
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