Advances in biomedical engineering /
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Edition: | 1st ed. |
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Imprint: | Amsterdam ; Boston : Elsevier, 2009. |
Description: | 1 online resource (xii, 280 pages, [24] pages of plates) : illustrations (some color) |
Language: | English |
Subject: | |
Format: | E-Resource Book |
URL for this record: | http://pi.lib.uchicago.edu/1001/cat/bib/11195872 |
Table of Contents:
- Preface
- List of Contributors
- 1. Review of Research in Cardiovascular Devices
- 1. Introduction
- 2. The Heart Diseases
- 3. The Cardiovascular Devices in Open-Heart Surgery
- 3.1. Blood Pumps
- 3.2. Valve Prostheses
- 3.3. Heart Pacemaker
- 4. The Minimally Invasive Cardiology Tools
- 5. The Technology for Atrial Fibrillation
- 6. Minimally Invasive Surgery
- 6.1. The Classical Thoracoscopic Tools
- 6.2. The Surgical Robots
- 6.3. Blood Pumps - MIS Application Study
- 7. The Minimally Invasive Valve Implantation
- 8. Support Technology for Surgery Planning
- 9. Conclusions
- 2. Biomechanical Modeling of Stents: Survey 1997-2007
- 1. Introduction
- 2. Finite Element Modeling of Stents
- 2.1. Finite element basics
- 2.2. Geometrical design and approximation
- 2.3. Material properties
- 2.4. Loading and boundary conditions
- 2.5. Finite element stent design
- 2.6. Effective use of FEA
- 3. Survey of the State of the Art in Stent Modeling: 1997-2007
- 3.1. Neglect of the balloon
- 3.2. Cylindrical balloon
- 3.3. Folded balloon
- 3.4. Summary
- 4. Alternative methods for biomechanical modeling of stents
- 4.1. FEM - Prolapse, flexibility and strut micromechanics
- 4.2. FEM - Self-expandable stents
- 4.3. CFD-drug elution and immersed FEM
- 5. Future Prospects
- 6. Conclusion
- 3. Signal Extraction in Multisensor Biomedical Recordings
- 1. Introduction
- 1.1. Aim and scope of the chapter
- 1.2. Mathematical notations
- 2. Genesis of Biomedical Signals
- 2.1. A biomedical source model
- 2.2. Cardiac signals
- 2.3. Brain signals
- 3. Multi-Reference Optimal Wiener Filtering
- 3.1. Non-invasive fetal ECG extraction
- 3.2. Optimal Wiener filtering
- 3.3. Adaptive noise cancellation
- 3.4. Results
- 4. Spatio-Temporal Cancellation
- 4.1. Atrial activity extraction in atrial fibrillation
- 4.2. Spatio-temporal cancellation of the QRST complex in AF episodes
- 5. Blind Source Separation (BSS)
- 5.1. The isolation of interictal epileptic discharges in the EEG
- 5.2. Modeling and assumptions
- 5.3. Inherent indeterminacies
- 5.4. Statistical independence, higher-order statistics and non-Gaussianity
- 5.5. Independent component analysis
- 5.6. Algorithms
- 5.7. Results
- 5.8. Incorporating prior information into the separation model
- 5.9. Independent subspaces
- 5.10. Softening the stationarity constraint
- 5.11. Revealing more sources than sensor signals
- 6. Summary, Conclusions and Outlook
- 4. Fluorescence Lifetime Spectroscopy and Imaging of Visible Fluorescent Proteins
- 1. Introduction
- 2. Introduction to Fluorescence
- 2.1. Interaction of light with matter
- 2.2. The Jablonski diagram
- 2.3. Fluorescence parameters
- 2.4. Fluorescence lifetime
- 2.5. Measurement of fluorescence lifetime
- 2.6. Fluorescence anisotropy and polarization
- 2.7. Factors affecting fluorescence
- 3. Fluorophores and Fluorescent Proteins
- 3.1. Green fluorescent protein
- 3.2. Red fluorescent protein
- 4. Applications of VFPs
- 4.1. Lifetime spectroscopy and imaging of VFPs
- 5. Concluding Remarks
- 5. Monte Carlo Simulations in Nuclear Medicine Imaging
- 1. Introduction
- 2. Nuclear Medicine Imaging
- 2.1. Single photon imaging
- 2.2. Positron emission tomography
- 2.3. Emission tomography in small animal imaging
- 2.4. Reconstruction
- 3. The MC Method
- 3.1. Random numbers
- 3.2. Sampling methods
- 3.3. Photon transport modeling
- 3.4. Scoring
- 4. Relevance of Accurate MC Simulations in Nuclear Medicine
- 4.1. Studying detector design
- 4.2. Analysing quantification issues
- 4.3. Correction methods for image degradations
- 4.4. Detection tasks using MC simulations
- 4.5. Applications in other domains
- 5. Available MC Simulators
- 6. Gate
- 6.1. Basic features
- 6.2. GATE: Time management
- 6.3. GATE: Digitization
- 7. Efficiency-Accuracy Trade-Off
- 7.1. Accuracy and validation
- 7.2. Calculation time
- 8. Case Studies
- 8.1. Case study I: TOF-PET
- 8.2. Case study II: Assessment of PVE correction
- 8.3. Case study III: MC-based reconstruction
- 9. Future Prospects
- 10. Conclusion
- 6. Biomedical Visualization
- 1. Introduction
- 2. Scalar Field Visualization
- 2.1. Direct volume rendering
- 2.2. Isosurface extraction
- 2.3. Time-dependent scalar field visualization
- 3. Vector Field Visualization
- 3.1. Vector field methods in scientific visualization
- 3.2. Streamline-based techniques
- 3.3. Stream surfaces
- 3.4. Texture representations
- 3.5. Topology
- 4. Tensor Field Visualization
- 4.1. Anisotropy and tensor invariants
- 4.2. Color coding of major eigenvector orientation
- 4.3. Tensor glyphs
- 4.4. Fiber tractography
- 4.5. Volume rendering
- 4.6. White matter segmentation using tensor invariants
- 5. Multi-field Visualization
- 6. Error and Uncertainty Visualization
- 7. Visualization Software
- 7.1. SCIRun/BioPSE visualization tools
- 7.2. map3d
- 8. Summary and Conclusion
- Index