: Krishnan B. Chandran, H. S. Udaykumar, Joseph M. Reinhardt
: Krishnan B. Chandran, H. S. Udaykumar, Joseph M. Reinhardt
: Image-Based Computational Modeling of the Human Circulatory and Pulmonary Systems Methods and Applications
: Springer-Verlag
: 9781441973504
: 1
: CHF 133.80
:
: Medizin
: English
: 465
: Wasserzeichen/DRM
: PC/MAC/eReader/Tablet
: PDF
Image-Based Computational Modeling of the Human Circulatory and Pulmonary Systems provides an overview of the current modeling methods and applications enhancing interventional treatments and computer-aided surgery. A detailed description of the techniques behind image acquisition, processing and three-dimensional reconstruction are included. Techniques for the computational simulation of solid and fluid mechanics and structure interaction are also discussed, in addition to various cardiovascular and pulmonary applications. Engineers and researchers involved with image processing and computational modeling of human organ systems will find this a valuable reference.
Foreword6
Preface8
Contents13
Contributors15
Part I Cardiac and Pulmonary Imaging, Image Processing, and Three-Dimensional Reconstruction in Cardiovascular and Pulmonary Systems19
1 Image Acquisition for Cardiovascular and Pulmonary Applications20
1.1 Introduction to Imaging20
1.1.1 Invasive Techniques22
1.1.2 Role of Noninvasive Imaging22
1.2 Ultrasound/Echocardiography23
1.2.1 Principles of Ultrasound23
1.2.1.1 M-Mode25
1.2.1.2 2D Ultrasound26
1.2.2 Echocardiography27
1.2.2.1 Morphologic Imaging27
1.2.2.2 Function28
1.2.2.3 Flow (Doppler)28
1.2.2.4 TTE Versus TEE29
1.2.3 Vascular/Peripheral30
1.3 Computed Tomography (CT)31
1.3.1 Principles of CT31
1.3.1.1 Basic CT32
1.3.1.2 Multidetector CT33
1.3.2 Cardiac CT34
1.3.2.1 Coronary Arteries34
1.3.2.2 Aorta35
1.3.2.3 Cardiac Function35
1.3.3 Pulmonary CT36
1.3.3.1 Parenchyma36
1.3.3.2 Pulmonary Angiography37
1.4 Magnetic Resonance Imaging (MRI)37
1.4.1 Principles of MRI37
1.4.1.1 Signal Generation38
1.4.1.2 General Techniques and Contrast Mechanisms38
1.4.1.3 Morphology39
1.4.1.4 Function40
1.4.1.5 Perfusion/Ischemia42
1.4.2 MR Angiography43
1.4.3 Pulmonary MRI: Emerging Techniques45
1.5 Other Techniques47
1.5.1 SPECT47
1.5.2 PET48
1.6 Summary49
References49
2 Three-dimensional and Four-dimensional Cardiopulmonary Image Analysis51
2.1 Introduction51
2.2 Segmentation and Modeling Methodology52
2.2.1 Active Shape and Appearance Models52
2.2.1.1 Building a 3D Statistical Shape Model53
2.2.1.2 Extension to Higher Dimensions54
2.2.1.3 Combining Shape and Appearance54
2.2.1.4 Robust ASM and AAM Implementations55
2.2.2 Region Growing and Fuzzy Connectivity Segmentation56
2.2.2.1 Region Growing56
2.2.2.2 Fuzzy Connectivity-Based Segmentation57
2.2.3 Graph-Based Segmentation58
2.2.3.1 Approaches Based on Rectangular Graph Structures58
2.2.3.2 Minimum-Cut Approaches61
2.2.3.3 Cost Functions62
2.3 Cardiac Applications63
2.3.1 Modeling and Quantitative Analysis of the Ventricles64
2.3.1.1 Manual Ventricle Segmentation64
2.3.1.2 3D Shape Generation66
2.3.2 Tetralogy of Fallot Classification68
2.3.2.1 Study Population and Experimental Methods69
2.3.2.2 Novel Ventricular Function Indices70
2.4 Vascular Applications71
2.4.1 Connective Tissue Disorder in the Aorta71
2.4.1.1 4D Segmentation of Aortic MR Image Data72
2.4.1.2 Disease Detection74
2.4.1.3 Accuracy of Segmentation and Classification75
2.4.2 Aortic Thrombus and Aneurysm Analysis76
2.4.2.1 Initial Luminal Surface Segmentation78
2.4.2.2 Graph Search and Cost Function Design79
2.4.2.3 Data and Results80
2.4.3 Plaque Distribution in Coronary Arteries83
2.4.3.1 Segmentation and 3D Fusion84
2.4.3.2 Hemodynamic and Morphologic Analysis88
2.4.3.3 Studies and Results89
2.5 Pulmonary Applications91
2.5.1 Segmentation and Quantitative Analysis of Airway Trees92
2.5.1.1 Airway Tree Segmentation93
2.5.1.2 Quantitative Analysis of Airway Tree Morphology95
2.5.2 Quantitative Analysis of Pulmonary Vascular Trees98
2.5.3 Segmentation of Lung Lobes104
2.6 Discussions and Conclusions107
References108
Part II Computational Techniques for Fluid and Soft Tissue Mechanics, FluidStructure Interaction, and Development of Multi-scale Simulations119
3 Computational Techniques for Biological Fluids: From Blood Vessel Scale to Blood Cells120
3.1 Introduction120
3.2 Computational Methods for Macro-scale Hemodynamics121
3.2.1 Governing Equations121
3.2.1.1 The Fluid Flow Equations121
3.2.1.2 The Structural Equations123
3.2.1.3 Boundary Conditions at the Fluid--Structure Interface126
3.2.2 Numerical Methods for Flows with Moving Boundaries126
3.2.2.1 Boundary-Conforming Methods127
3.2.2.2 Non-boundary-Conforming Methods129
3.2.2.3 Hybrid Methods: Body-Fitted/Immersed Boundary Methods133
3.2.3 Fluid--Structure Interaction Algorithms133
3.2.3.1 Loose and Strong Coupling Strategies134
3.2.3.2 Stability and Robustness Issues135
3.2.4 Efficient Solvers for Physiologic Pulsatile Simulations136
3.2.5 High-Resolution Simulations of Cardiovascular Flow137
3.2.5.1 Fluid--Structure Interaction Simulations of Mechanical Bileaflet Heart Valves137
3.2.5.2 Numerical Simulations of Trileaflet Heart Valve Hemodynamics139
3.3 Computational Methods for Blood Cell Scale Simulations142
3.3.1 Background142
3.3.2 Review of Numerical Methods for Blood Cell-Resolving Simulations142
3.3.2.1 Boundary-Integral Methods for Cell-Level Simulation143
3.3.2.2 Immersed Boundary Method144
3.3.2.3 Particle Methods144
3.3.2.4 Lattice Boltzmann145
3.3.3 Lattice-Boltzmann Methodology145
3.3.3.1 Lattice-Boltzmann BGK (LBGK) Model for Fluid Flow145
3.3.3.2 Transient Finite-Element FSI Model146
3.3.4 Membrane Models151
3.3.4.1 Comparison of Red Blood Cell Models154
3.3.5 Rheology, Stress, and Microstructure of Blood154
3.3.5.1 Bulk Rheology155
3.3.5.2 Shear-Thinning Behavior156
3.3.5.3 Microstructure158
3.3.5.4 Local Stress Environment in Blood161
3.4 Future Directions162
References163
4 Formulation and Computational Implementation of Constitutive Models for Cardiovascular Soft Tissue Simulations171
4.1 Introduction171
4.2 Constitutive Models for Cardiovascular Soft Tissues173
4.2.1 Condition Number of D176
4.3 Structural Constitutive Models