544 pages | 300 B/W Illus.
Medical Image Processing, Reconstruction and Analysis – Concepts and Methods explains the general principles and methods of image processing, focusing namely on applications used in medical imaging – providing a theoretical yet clear and easy to follow explanation of underlying generic concepts.
The content of this book is divided into three parts:
Part 1: 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. Discrete Two-Dimensional Operators. Discrete Two-Dimensional Linear Transforms. Discrete Stochastic Images. Part II: Imaging Systems as Data Sources Planar X-Ray Imaging. X-Ray Projection Radiography. Subtractive Angiography. X-Ray Comuted 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 Impedence Tomography. 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 and Future Trends in Medical Image Processing.