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BL
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| Record Number
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888993
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| Main Entry
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Wang, Shui-Hua
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| Title & Author
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Pathological brain detection /\ Shui-Hua Wang, Yu-Dong Zhang, Zhengchao Dong, Preetha Phillips.
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| Publication Statement
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Singapore :: Springer,, 2018.
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| Series Statement
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Brain informatics and health
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| Page. NO
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1 online resource
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| ISBN
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9789811040252
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: 9789811040269
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: 9789811040276
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: 9789811338342
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: 9811040257
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: 9811040265
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: 9811040273
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: 9811338345
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9789811040252
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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Intro; Preface; Acknowledgements; Contents; Acronyms; List of Figures; 1 Basics of Pathological Brain Detection; 1.1 History; 1.2 Brain Diseases; 1.2.1 Neoplastic Disease; 1.2.2 Neurodegeneration; 1.2.3 Cerebrovascular Disease; 1.2.4 Inflammation; 1.2.5 Summary; 1.3 A Standard Computer-Aided Diagnosis System; 1.4 Research Trends; References; 2 Neuroimaging Modalities; 2.1 History of Neuroimaging; 2.1.1 Pneumoencephalography; 2.1.2 Cerebral Angiography; 2.1.3 Computerized Tomography; 2.1.4 Positron Emission Tomography; 2.1.5 Single-Photon Emission Computed Tomography
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2.2 Magnetic Resonance Imaging2.2.1 Projectile Risk; 2.2.2 Shimming; 2.2.3 Water and Fat Suppression; 2.2.4 Two Types of Contrast; 2.2.5 Interpretation; 2.3 Other Magnetic Resonance Imaging Modalities; 2.3.1 Diffusion Tensor Imaging; 2.3.2 Functional Magnetic Resonance Imaging; 2.3.3 Magnetic Resonance Angiography; 2.3.4 Magnetic Resonance Spectroscopic Imaging; 2.4 Conclusion; References; 3 Image Preprocessing for Pathological Brain Detection; 3.1 k-Space; 3.2 Image Denoising; 3.2.1 Rician Noise; 3.2.2 Solutions; 3.2.3 Wiener Filter; 3.2.4 Wavelet-Based Denoising; 3.3 Skull Stripping
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3.3.1 Software Library at the Oxford Centre for Functional MRI of the Brain3.3.2 Statistical Parametric Mapping; 3.3.3 Other Means; 3.4 Slice Selection; 3.5 Spatial Normalization; 3.5.1 FSL Solution; 3.5.2 Matlab Solution; 3.6 Intensity Normalization; 3.7 Image Enhancement; 3.7.1 Histogram Equalization; 3.7.2 Contrast-Limited Adaptive Histogram Equalization; 3.8 Conclusion; References; 4 Canonical Feature Extraction Methods for Structural Magnetic Resonance Imaging; 4.1 Shape Feature; 4.2 Statistical Measure; 4.2.1 Common Measures; 4.2.2 Statistical Chart; 4.3 Image Moments; 4.3.1 Raw Moments
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4.3.2 Central Moments4.3.3 Normalized Central Moments; 4.3.4 Hu Moment Invariants; 4.4 Zernike Moments; 4.4.1 Basic Form of Zernike Moments; 4.4.2 Pseudo Zernike Moment; 4.4.3 Coordinate Transform; 4.4.4 Illustration of Pseudo Zernike Polynomials; 4.5 Gray-Level Co-occurrence Matrix; 4.6 Fourier Transform; 4.6.1 Discrete Fourier Transform; 4.6.2 Discrete Sine and Cosine Transform; 4.7 Fractional Fourier Transform; 4.7.1 Unified Time-Frequency Domain; 4.7.2 Weighted-Type Fractional Fourier Transform; 4.7.3 Sampling-Type Fractional Fourier Transform
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4.7.4 Eigendecomposition-Type Fractional Fourier Transform4.8 Entropy; 4.8.1 Shannon Entropy; 4.8.2 Tsallis Entropy; 4.8.3 Renyi Entropy; 4.9 Conclusion; References; 5 Multi-scale and Multi-resolution Features for Structural Magnetic Resonance Imaging; 5.1 Wavelet Transform; 5.1.1 Development of Signal Processing; 5.1.2 Potential Application to Pathological Brain Detection; 5.2 Continuous Wavelet Transform and Discrete Wavelet Transform; 5.2.1 Mathematical Analysis of a Continuous Wavelet Transform; 5.2.2 Koch Curve Example of the Continuous Wavelet Transform; 5.2.3 Discrete Wavelet Transform
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| Abstract
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This book provides detailed practical guidelines on how to develop an efficient pathological brain detection system, reflecting the latest advances in the computer-aided diagnosis of structural magnetic resonance brain images. Matlab codes are provided for most of the functions described. In addition, the book equips readers to easily develop the pathological brain detection system further on their own and apply the technologies to other research fields, such as Alzheimer's detection, multiple sclerosis detection, etc.
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| Subject
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Computational neuroscience.
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Machine learning.
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Neuroinformatics.
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Brain-- physiopathology.
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Medical Informatics.
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Computational neuroscience.
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HEALTH FITNESS-- Diseases-- General.
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Machine learning.
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MEDICAL-- Clinical Medicine.
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MEDICAL-- Diseases.
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MEDICAL-- Evidence-Based Medicine.
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MEDICAL-- Internal Medicine.
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| Subject
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Neuroinformatics.
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| Dewey Classification
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616.800285
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| LC Classification
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QP357.5
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| NLM classification
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WL 26.5
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| Added Entry
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Dong, Zhengchao
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Phillips, Preetha
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Zhang, Yu-Dong
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