Cardiovascular and respiratory bioengineering

Cardiovascular and Respiratory Bioengineering focuses on computational tools and modeling techniques in cardiovascular and respiratory systems that help develop bioengineered solutions. The book demonstrates how these technologies can be utilized in order to tackle diseases and medical issues. It pr...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Filipovic, Nenad, 1970-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London : Academic Press, 2022.
Temas:
Cardiovascular system > Computer simulation.
Cardiovascular system > Mathematical models.
Respiratory organs > Computer simulation.
Respiratory organs > Mathematical models.
Bioengineering.
Biotechnology
Appareil cardiovasculaire > Simulation par ordinateur.
Appareil cardiovasculaire > Mod�eles math�ematiques.
Appareil respiratoire > Simulation par ordinateur.
Appareil respiratoire > Mod�eles math�ematiques.
Biotechnologie.
bioengineering.
Bioengineering
Cardiovascular system > Computer simulation
Cardiovascular system > Mathematical models
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Intro
  • Cardiovascular and Respiratory Bioengineering
  • Copyright
  • Contents
  • Contributors
  • Preface
  • Chapter 1: Computational modeling of electromechanical coupling of left ventricle
  • 1. Introduction
  • 2. Method
  • 2.1. Fluid-solid coupling
  • 2.2. Nonlinear material model of the left ventricle
  • 2.2.1. Biaxial tests
  • 2.2.2. Shear tests
  • 2.3. Electrophysiology of the left ventricle
  • 3. Results
  • 3.1. Geometry of the left ventricle with a shorter base length
  • 3.1.1. Scenario1a: Influence of Ca2+ concentration
  • 3.1.2. Scenario 2a: Influence of the Holzapfel scale factor (elasticity)
  • 3.1.3. Scenario 3a: Influence of inlet and outlet velocities
  • References
  • Chapter 2: Deep learning approach in ultrasound image segmentation for patients with carotid artery disease
  • 1. Introduction
  • 2. Carotid artery and personalized medicine
  • 3. Previous approaches in medical image segmentation
  • 3.1. The traditional image processing approach
  • 3.2. Deep convolution neural networks
  • 4. Dataset acquisition and description
  • 5. Methodology
  • 5.1. Lumen and wall detection
  • 5.2. Carotid plaque characterization
  • 6. Results
  • 7. Conclusions
  • Acknowledgments
  • References
  • Chapter 3: Simulation of stent mechanical testing
  • 1. Introduction
  • 2. Methodology
  • 2.1. PAK software
  • 2.2. Finite element model for SYNERGY BP
  • 2.3. Material model
  • 3. Results
  • 3.1. Inflation test
  • 3.2. Radial force test
  • 3.3. Crush test with two plates
  • 3.4. Local compression
  • 3.4.1. Longitudinal tensile strength
  • 3.5. Three-point bending
  • 4. Conclusions
  • References
  • Chapter 4: ECG simulation of cardiac hypertrophic condition
  • 1. Introduction
  • 2. Anatomy of the heart
  • 2.1. The structure of the heart
  • 2.1.1. The outer structure of the heart
  • 2.1.2. The inner structure of the heart
  • 2.2. Cardiac circulation
  • 2.2.1. Arterial system of the heart
  • 2.3. Cardiac physiology
  • 3. Electrocardiography
  • 3.1. Twelve-channel ECG
  • 4. Cardiomyopathy
  • 4.1. Dilated or congestive cardiomyopathy
  • 4.2. Restrictive cardiomyopathy
  • 4.3. Hypertrophic cardiomyopathy
  • 4.4. Diagnostic techniques
  • 4.4.1. Electrocardiography
  • 4.4.2. Echocardiography
  • 4.4.3. Magnetic resonance
  • 4.4.4. Computed tomography angiography
  • 4.4.5. Heart catheterization
  • 4.5. Differential diagnosis
  • 4.6. Treatment
  • 4.6.1. Drug treatment
  • 4.6.2. Electrostimulation of the heart
  • 4.6.3. Surgical treatment
  • 5. Anatomical model
  • 6. Numerical model
  • 7. Results
  • 8. Conclusions
  • References
  • Chapter 5: Simulation of carotid artery plaque development and treatment
  • 1. Introduction
  • 2. Materials and methods
  • 2.1. Clinical dataset
  • 2.2. Segmentation and plaque classification using deep learning
  • 2.3. Three-dimensional reconstruction
  • 2.4. Blood flow and plaque progression simulation

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