| Titre : | Advanced signal processing handbook : theory and implementation for radar, sonar, and medical imaging Real time system | | Type de document : | texte imprimé | | Auteurs : | Stergios Stergiopoulos, Auteur | | Editeur : | Boca Raton; London; New York : CRC Press | | Année de publication : | 2001 | | Collection : | The Electrocal ana Signal Processing Series | | Importance : | 666 p. | | Présentation : | couv. ill. en en coul | | Format : | 26 cm. | | ISBN/ISSN/EAN : | 978-0-84933-691-1 | | Langues : | Anglais (eng) | | Catégories : | GÉNÉRALITÉ
| | Index. décimale : | 00-07 HandBook | | Résumé : | Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far beyond those of just few years ago. Nonlinear, adaptive methods for signal processing have emerged to provide better array gain performance, however, they lack the robustness of conventional algorithms. The challenge remains to develop a concept that exploits the advantages of both-a scheme that integrates these methods in practical, real-time systems.
The Advanced Signal Processing Handbook helps you meet that challenge. Beyond offering an outstanding introduction to the principles and applications of advanced signal processing, it develops a generic processing structure that takes advantage of the similarities that exist among radar, sonar, and medical imaging systems and integrates conventional and nonlinear processing schemes. | | Note de contenu : | Contents
1 Signal Processing Concept Similarities among Sonar, Radar,and Medical Imaging Systems Stergios Stergiopoulos
1.2 Overview of a Real-Time System
1.3 Signal Processor
1.4 Data Manager and Display Sub-System
SECTION I General Topics on Signal Processing
2 Adaptive Systems for Signal Process
2.1 The Filtering Problem
2.2 Adaptive Filters
2.3 Linear Filter Structures
2.4 Approaches to the Development of Linear Adaptive Filtering Algorithms
2.5 Real and Complex Forms of Adaptive Filters
2.6 Nonlinear Adaptive Systems: Neural Networks
2.7 Applications
2.8 Concluding Remarks
3 Gaussian Mixtures and Their Applications to Signal Processing
3.2 Mathematical Aspects of Gaussian Mixtures
3.3 Methodologies for Mixture Parameter Estimation
3.4 Computer Generation of Mixture Variables
3.5 Mixture Applications
3.6 Concluding Remarks
4 Matched Field Processing — A Blind System Identification Technique
4.2 Blind System Identification
4.3 Cross-Relation Matched Field Processor
4.4 Time-Frequency Matched Field Processor
4.5 Higher Order Matched Field Processors
4.6 Simulation and Experimental Examples
5 Model-Based Ocean Acoustic Signal Processing
5.2 Model-Based Processing
5.3 State-Space Ocean Acoustic Forward Propagators
5.4 Ocean Acoustic Model-Based Processing Applications
6 Advanced Beamformers Stergios Stergiopoulos
6.2 Background
6.3 Theoretical Remarks
6.4 Optimum Estimators for Array Signal Processing
6.5 Advanced Beamformers
6.6 Implementation Considerations
6.7 Concept Demonstration: Simulations and Experimental Results
7 Advanced Applications of Volume Visualization Methods in Medicine
7.1 Volume Visualization Principles
7.2 Applications to Medical Data
Appendix Principles of Image Processing: Pixel Brightness Transformations,Image Filtering and Image Restoration
8 Target Tracking
8.2 Discussion of the Problem
8.3 Statistical Models
8.4 Bayesian Track Maintenance
8.5 Suboptimal Realization
8.6 Selected Applications
9 Target Motion Analysis (TMA)
9.2 Features of the TMA Problem
9.3 Solution of the TMA Problem
SECTION II Sonar and Radar System Applications
10 Sonar Systems
10.2 Underwater Propagation
10.3 Underwater Sound Systems: Components and Processes
10.4 Signal Processing Functions
10.5 Advanced Signal Processing
10.6 Application
11 Theory and Implementation of Advanced Signal Processing for Active and Passive Sonar Systems
11.2 Theoretical Remarks
11.3 Real Results from Experimental Sonar Systems
12 Phased Array Radars Nikolaos Uzunoglu
12.2 Fundamental Theory of Phased Arrays
12.3 Analysis and Design of Phased Arrays
12.4 Array Architectures
SECTION III Medical Imaging System Applications
13 Medical Ultrasonic Imaging Systems John M. Reid
13.2 System Fundamentals
13.3 Tissue Properties’ Influence on System Design
13.4 Imaging Systems
14 Basic Principles and Applications of 3-D Ultrasound Imaging
14.2 Limitations of Ultrasonography Addressed by 3-D Imaging
14.3 Scanning Techniques for 3-D Ultrasonography
14.4 Reconstruction of the 3-D Ultrasound Images
14.5 Sources of Distortion in 3-D Ultrasound Imaging
14.6 Viewing of 3-D Ultrasound Images
14.7 3-D Ultrasound System Performance
14.8 Use of 3-D Ultrasound in Brachytherapy
14.9 Trends and Future Developments
15 Industrial Computed Tomographic Imaging
15.2 CT Theory and Fundamentals
15.3 Selected Applications
15.5 Future Work
16 Organ Motion Effects in Medical CT Imaging Applications
16.2 Motion Artifacts in CT
16.3 Reducing Motion Artifacts
16.4 Reducing Motion Artifacts by Signal Processing — A Synthetic Aperture Approach
17 Magnetic Resonance Tomography — Imaging with a Nonlinear System
17.2 Basic NMR Phenomena
17.3 Relaxation
17.4 NMR Signal
17.5 Signal-to-Noise Ratio
17.6 Image Generation and Reconstruction
17.7 Selective Excitation
17.8 Pulse Sequences
17.9 Influence of Motion
17.10 Correction of Motion During Image Series
17.11 Imaging of Flow
17.12 MR Spectroscopy
17.13 System Design Considerations and Conclusions
18 Functional Imaging of Tissues by Kinetic Modeling of Contrast Agents in MRI
18.2 Contrast Agent Kinetic Modeling
18.3 Measurement of Contrast Agent Concentration
18.4 Application of T1 Farm to Bolus Tracking
19 Medical Image Registration and Fusion Techniques: A Review
19.2 Medical Image Registration
19.3 Medical Image Fusion
20 The Role of Imaging in Radiotherapy Treatment Planning
20.2 The Role of Imaging in the External Beam Treatment Planning
20.3 Introduction to Imaging Based Brachytherapy
20.4 Conclusion |
Advanced signal processing handbook : theory and implementation for radar, sonar, and medical imaging Real time system [texte imprimé] / Stergios Stergiopoulos, Auteur . - Boca Raton; London; New York : CRC Press, 2001 . - 666 p. : couv. ill. en en coul ; 26 cm.. - ( The Electrocal ana Signal Processing Series) . ISBN : 978-0-84933-691-1 Langues : Anglais ( eng) | Catégories : | GÉNÉRALITÉ
| | Index. décimale : | 00-07 HandBook | | Résumé : | Advances in digital signal processing algorithms and computer technology have combined to produce real-time systems with capabilities far beyond those of just few years ago. Nonlinear, adaptive methods for signal processing have emerged to provide better array gain performance, however, they lack the robustness of conventional algorithms. The challenge remains to develop a concept that exploits the advantages of both-a scheme that integrates these methods in practical, real-time systems.
The Advanced Signal Processing Handbook helps you meet that challenge. Beyond offering an outstanding introduction to the principles and applications of advanced signal processing, it develops a generic processing structure that takes advantage of the similarities that exist among radar, sonar, and medical imaging systems and integrates conventional and nonlinear processing schemes. | | Note de contenu : | Contents
1 Signal Processing Concept Similarities among Sonar, Radar,and Medical Imaging Systems Stergios Stergiopoulos
1.2 Overview of a Real-Time System
1.3 Signal Processor
1.4 Data Manager and Display Sub-System
SECTION I General Topics on Signal Processing
2 Adaptive Systems for Signal Process
2.1 The Filtering Problem
2.2 Adaptive Filters
2.3 Linear Filter Structures
2.4 Approaches to the Development of Linear Adaptive Filtering Algorithms
2.5 Real and Complex Forms of Adaptive Filters
2.6 Nonlinear Adaptive Systems: Neural Networks
2.7 Applications
2.8 Concluding Remarks
3 Gaussian Mixtures and Their Applications to Signal Processing
3.2 Mathematical Aspects of Gaussian Mixtures
3.3 Methodologies for Mixture Parameter Estimation
3.4 Computer Generation of Mixture Variables
3.5 Mixture Applications
3.6 Concluding Remarks
4 Matched Field Processing — A Blind System Identification Technique
4.2 Blind System Identification
4.3 Cross-Relation Matched Field Processor
4.4 Time-Frequency Matched Field Processor
4.5 Higher Order Matched Field Processors
4.6 Simulation and Experimental Examples
5 Model-Based Ocean Acoustic Signal Processing
5.2 Model-Based Processing
5.3 State-Space Ocean Acoustic Forward Propagators
5.4 Ocean Acoustic Model-Based Processing Applications
6 Advanced Beamformers Stergios Stergiopoulos
6.2 Background
6.3 Theoretical Remarks
6.4 Optimum Estimators for Array Signal Processing
6.5 Advanced Beamformers
6.6 Implementation Considerations
6.7 Concept Demonstration: Simulations and Experimental Results
7 Advanced Applications of Volume Visualization Methods in Medicine
7.1 Volume Visualization Principles
7.2 Applications to Medical Data
Appendix Principles of Image Processing: Pixel Brightness Transformations,Image Filtering and Image Restoration
8 Target Tracking
8.2 Discussion of the Problem
8.3 Statistical Models
8.4 Bayesian Track Maintenance
8.5 Suboptimal Realization
8.6 Selected Applications
9 Target Motion Analysis (TMA)
9.2 Features of the TMA Problem
9.3 Solution of the TMA Problem
SECTION II Sonar and Radar System Applications
10 Sonar Systems
10.2 Underwater Propagation
10.3 Underwater Sound Systems: Components and Processes
10.4 Signal Processing Functions
10.5 Advanced Signal Processing
10.6 Application
11 Theory and Implementation of Advanced Signal Processing for Active and Passive Sonar Systems
11.2 Theoretical Remarks
11.3 Real Results from Experimental Sonar Systems
12 Phased Array Radars Nikolaos Uzunoglu
12.2 Fundamental Theory of Phased Arrays
12.3 Analysis and Design of Phased Arrays
12.4 Array Architectures
SECTION III Medical Imaging System Applications
13 Medical Ultrasonic Imaging Systems John M. Reid
13.2 System Fundamentals
13.3 Tissue Properties’ Influence on System Design
13.4 Imaging Systems
14 Basic Principles and Applications of 3-D Ultrasound Imaging
14.2 Limitations of Ultrasonography Addressed by 3-D Imaging
14.3 Scanning Techniques for 3-D Ultrasonography
14.4 Reconstruction of the 3-D Ultrasound Images
14.5 Sources of Distortion in 3-D Ultrasound Imaging
14.6 Viewing of 3-D Ultrasound Images
14.7 3-D Ultrasound System Performance
14.8 Use of 3-D Ultrasound in Brachytherapy
14.9 Trends and Future Developments
15 Industrial Computed Tomographic Imaging
15.2 CT Theory and Fundamentals
15.3 Selected Applications
15.5 Future Work
16 Organ Motion Effects in Medical CT Imaging Applications
16.2 Motion Artifacts in CT
16.3 Reducing Motion Artifacts
16.4 Reducing Motion Artifacts by Signal Processing — A Synthetic Aperture Approach
17 Magnetic Resonance Tomography — Imaging with a Nonlinear System
17.2 Basic NMR Phenomena
17.3 Relaxation
17.4 NMR Signal
17.5 Signal-to-Noise Ratio
17.6 Image Generation and Reconstruction
17.7 Selective Excitation
17.8 Pulse Sequences
17.9 Influence of Motion
17.10 Correction of Motion During Image Series
17.11 Imaging of Flow
17.12 MR Spectroscopy
17.13 System Design Considerations and Conclusions
18 Functional Imaging of Tissues by Kinetic Modeling of Contrast Agents in MRI
18.2 Contrast Agent Kinetic Modeling
18.3 Measurement of Contrast Agent Concentration
18.4 Application of T1 Farm to Bolus Tracking
19 Medical Image Registration and Fusion Techniques: A Review
19.2 Medical Image Registration
19.3 Medical Image Fusion
20 The Role of Imaging in Radiotherapy Treatment Planning
20.2 The Role of Imaging in the External Beam Treatment Planning
20.3 Introduction to Imaging Based Brachytherapy
20.4 Conclusion |
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Advanced signal processing handbook / Stergios Stergiopoulos
