Advances in biomedical engineering /

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Bibliographic Details
Edition:1st ed.
Imprint:Amsterdam ; Boston : Elsevier, 2009.
Description:1 online resource (xii, 280 pages, [24] pages of plates) : illustrations (some color)
Language:English
Subject:Biomedical engineering.
Biomedical engineering -- Study and teaching.
Biomedical engineering -- Research.
Biomedical Engineering.
TECHNOLOGY & ENGINEERING -- Biomedical.
MEDICAL -- Family & General Practice.
MEDICAL -- Allied Health Services -- Medical Technology.
MEDICAL -- Biotechnology.
MEDICAL -- Lasers in Medicine.
Biomedical engineering.
Biomedical engineering -- Research.
Biomedical engineering -- Study and teaching.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/11195872
Hidden Bibliographic Details
Other authors / contributors:Verdonck, P.
ISBN:9780444530752
0444530754
9780080932088
0080932088
Notes:Includes bibliographical references and index.
Print version record.
Summary:The aim of this essential reference is to bring together the interdisciplinary areas of biomedical engineering education. Contributors review the latest advances in biomedical engineering research through an educational perspective, making the book useful for students and professionals alike. Topics range from biosignal analysis and nanotechnology to biophotonics and cardiovascular medical devices. - Provides an educational review of recent advances - Focuses on biomedical high technology - Features contributions from leaders in the field.
Other form:Print version: Advances in biomedical engineering. 1st ed. Amsterdam ; Boston : Elsevier, 2009 9780444530752 0444530754
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