Medical Image Processing, Reconstruction and Analysis: Concepts and Methods, Second Edition 2nd New edition [Kietas viršelis]

(Brno University of Technology, FEEC, Brno, Czech Republic)
  • Formatas: Hardback, 572 pages, aukštis x plotis: 254x178 mm, 1 Tables, black and white; 300 Illustrations, black and white
  • Serija: Signal Processing and Communications 2
  • Išleidimo metai: 13-Aug-2019
  • Leidėjas: CRC Press
  • ISBN-10: 113831028X
  • ISBN-13: 9781138310285
Kitos knygos pagal šią temą:
  • Formatas: Hardback, 572 pages, aukštis x plotis: 254x178 mm, 1 Tables, black and white; 300 Illustrations, black and white
  • Serija: Signal Processing and Communications 2
  • Išleidimo metai: 13-Aug-2019
  • Leidėjas: CRC Press
  • ISBN-10: 113831028X
  • ISBN-13: 9781138310285
Kitos knygos pagal šią temą:
Differently oriented specialists and students involved in image processing and analysis need to have a firm grasp of concepts and methods used in this now widely utilized area. This book aims at being a single-source reference providing such foundations in the form of theoretical yet clear and easy to follow explanations of underlying generic concepts.Medical Image Processing, Reconstruction and Analysis – Concepts and Methods explains the general principles and methods of image processing and analysis, focusing namely on applications used in medical imaging. 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 representations.Part II – Imaging Systems as Data Sources offers a non-traditional view on imaging modalities, explaining their principles influencing properties of the obtained images that are to be subsequently processed by methods described in this book. Newly, principles of novel modalities, as spectral CT, functional MRI, ultrafast planar-wave ultrasonography and optical coherence tomography are included. Part III – Image Processing and Analysis focuses on tomographic image reconstruction, image fusion and methods of image enhancement and restoration; further it explains concepts of low-level image analysis as texture analysis, image segmentation and morphological transforms. A new chapter deals with selected areas of higher-level analysis, as principal and independent component analysis and particularly the novel analytic approach based on deep learning. Briefly, also the medical image-processing environment is treated, including processes for image archiving and communication. Features Presents a theoretically exact yet understandable explanation of image processing and analysis concepts and methodsOffers practical interpretations of all theoretical conclusions, as derived in the consistent explanation Provides a concise treatment of a wide variety of medical imaging modalities including novel ones, with respect to properties of provided image data
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.
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.