Medical Image Processing, Reconstruction and Restoration: Concepts and Methods

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Overview

It is essential that differently oriented specialists and students involved in image processing have a firm grasp of the necessary concepts and principles. A single-source reference that can provide this foundation, as well as a thorough explanation of the techniques involved, particularly those found in medical image processing, would be an invaluable resource to have.

Medical Image Processing, Reconstruction and Restoration: Concepts and Methods is that resource. It not only explains the general principles and methods of image processing, but also focuses on recent applications specific to medical imaging – providing a theoretical yet clear explanation of underlying generic concepts.

The content of this book is divided into three parts:

  • Part I, Images as Multidimensional Signals, provides the introduction to basic image processing theory, explaining it for both analogue and digital image representation.
  • Part II, Imaging Systems as Data Sources, offers an alternative view on imaging modalities, with emphasis placed on analyzing internal signals and (pre)image data that are consequently processed.
  • Part III, Image Processing and Analysis, focuses on such vital image processing topics as tomographic image reconstruction, image fusion, methods of image enhancement, and image restoration techniques. This section also explains concepts of fundamental-level image analysis – detailing local feature analysis, image segmentation, and generalized morphological transforms. It also addresses what is needed within the image processing environment by noting necessary hardware and software and processes for image archiving and communications.
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Product Details

Table of Contents

PART I: IMAGES AS MULTIDIMENSIONAL SIGNALS
ANALOGUE (CONTINUOUS-SPACE) IMAGE REPRESENTATION
Multidimensional Signals as Image Representation
Two-Dimensional Fourier Transform
Two-Dimensional Continuous-Space Systems
Concept of Stochastic Images
DIGITAL IMAGE REPRESENTATION
Digital Image Representation
Discrete Two-Dimensional Operators
Discrete Two-Dimensional Linear Transforms
Discrete Stochastic Images
REFERENCES
PART II: IMAGING SYSTEMS AS DATA SOURCES
PLANAR X-RAY IMAGING
X-Ray Projection Radiography
Subtractive Angiography
X-RAY COMPUTED TOMOGRAPHY
Imaging Principle and Geometry
Measuring Considerations
Imaging Properties
Postmeasurement Data Processing in Computed Tomography
MAGNETIC RESONANCE IMAGING
Magnetic Resonance Phenomena
Response Measurement and Interpretation
Basic MRI Arrangement
Localization and Reconstruction of Image Data
Image Quality and Artifacts
Postmeasurement Data Processing in MRI
NUCLEAR IMAGING
Planar Gamma Imaging
Single-Photon Emission Tomography
Positron Emission Tomography
ULTRASONOGRAPHY
Two-Dimensional Echo Imaging
Flow Imaging
Three-Dimensional Ultrasonography
OTHER MODALITIES
Optical and Infrared Imaging
Electron Microscopy
Electrical Impedance Tomography
REFERENCES
PART III: IMAGE PROCESSING AND ANALYSIS
RECONSTRUCTING TOMOGRAPHIC IMAGES
Reconstruction from Near-Ideal Projections
Reconstruction from Nonideal Projections
Other Approaches to Tomographic Reconstruction
IMAGE FUSION
Ways to Consistency
Disparity Analysis
Image Registration
Image Fusion
IMAGE ENHANCEMENT
Contrast Enhancement
Sharpening and Edge Enhancement
Noise Suppression
Geometrical Distortion Correction
IMAGE RESTORATION
Correction of Intensity Distortions
Geometrical Restitution
Inverse Filtering
Restoration Methods Based on Optimization
Homomorphic Filtering and Deconvolution
IMAGE ANALYSIS
Local Feature Analysis
Image Segmentation
General Morphological Transforms
MEDICAL IMAGE PROCESSING ENVIRONMENT
Hardware and Software Features
Principles of Image Compression for Archiving
and Communication
Present Trends in Medical Image Processing
REFERENCES

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