Medical Image Processing, Reconstruction and Analysis: Concepts and Methods, Second Edition, 2nd Edition (Hardback) book cover

Medical Image Processing, Reconstruction and Analysis

Concepts and Methods, Second Edition, 2nd Edition

By Jiri Jan

CRC Press

544 pages | 300 B/W Illus.

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Hardback: 9781138310285
pub: 2019-08-13
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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 IImages as Multidimensional Signals provides the introduction tobasic image processing theory, explaining it for both analogue and digital image representations.
  • Part IIImaging Systems as Data Sources offers a non-traditional view on imaging modalities, explaining – without technical details – their basic principles influencing the properties of the obtained images, with emphasis placed on analyzing the internal signals and (pre)image data that are to be processed by the methods described in this book.
  • Part IIIImage Processing and Analysis focuses on such vital image processing topics as tomographic image reconstruction, image fusion, methods if image enhancement and restoration. It explains concepts of both fundamental-level image analysis detailing local feature, edge and texture analysis, image segmentation and morphological transforms, and higher-level analysis, as principal and independent component analysis and namely the new analysis area based on deep learning, namely that using convolutional neural networks. Briefly, also the medical image-processing environment is briefly treated, including the processes for image archiving and communication.


  • Presents a good, theoretically exact yet understandable overview of basic theory related to image processing and analysis, with practical interpretations of all theoretical conclusions
  • Provides a concise treatment of a wide variety of medical imaging modalities with respect to properties of image data to be processed
  • Includes topical discussions on medical image reconstruction, fusion, enhancement and restoration as well as on image analysis including the recently appearing deep-learning based methods
  • Explores appropriate applications relevant to particular chapters

Table of Contents

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.

About the Author

Jiri Jan is a full Professor within the Department of Biomedical Engineering at Brno University in the Czech Republic. He has been an active researcher and educator in medical image processing and analysis over the past thirty years. He is the founding president of the European Association of Medical Imaging and has written over 200 peer reviewed journal articles, 30 book chapters and authored/edited four books within medical imaging.

About the Series

Signal Processing and Communications

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Subject Categories

BISAC Subject Codes/Headings:
MEDICAL / General
MEDICAL / Biotechnology
SCIENCE / Research & Methodology