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视网膜光学相干断层成像分析(英文版)
  • 书号:9787030587237
    作者:
  • 外文书名:
  • 丛书名:
  • 装帧:圆脊精装
    开本:B5
  • 页数:401
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    语种:en
  • 出版社:科学出版社
    出版时间:1900-01-01
  • 所属分类:
  • 定价: ¥299.00元
    售价: ¥239.20元
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目录

  • Contents
    Preface
    Chapter 1 Clinical Applications of Retinal Optical Coherence
    1.1 Anatomy of the Eye and Retina 1
    1.1.1 Simple Anatomy of the Eye 1
    1.1.2 Simple Histology of Retina 2
    1.1.3 Normal Macular OCT Image 4
    1.2 Vitreomacular Interface Diseases 5
    1.2.1 Vitreomacular Adhesion 5
    1.2.2 Vitreomacular Traction 6
    1.2.3 Full Thickness Macular Hole (FTMH) 7
    1.2.4 Epiretinal Membrane 8
    1.2.5 Myopic Traction Maculopathy 10
    1.3 Glaucoma and Optic Neuropathy 10
    1.3.1 Parapapillary Retinal Nerve Fiber Layer Thickness 11
    1.3.2 Macular Ganglion Cell Thickness 11
    1.3.3 0ptic Nerve Head Morphology 12
    1.4 Retinal Vascular Diseases 14
    1.4.1 Retinal Artery Occlusion 14
    1.4.2 Diabetic Retinopathy 15
    1.4.3 Retinal Vein Occlusion 16
    1.5 0uter Retinal Degenerative Diseases 19
    1.6 Choroidal Neovascularization and Polypoidal Choroidal
    Chapter 2 Fundamentals of Retinal Optical Coherence Tomography 26
    2.1 Introduction 26
    2.2 Developments and Principles of Operation of Optical Coherence
    2.2.1 Time Domain OCT 27
    2.2.2 Fourier Domain OCT 28
    2.2.3 0ther Evolving OCT Technologies 30
    2.3 Interpretation of the Optical Coherence Tomography Image 32
    Chapter 3 Speckle Noise Reduction and Enhancement for OCT
    Images 38
    3.1.2 Speckle Properties 40
    3.2 0CT Image Modeling 41
    3.3 Statistical Model for OCT Contrast Enhancement 47
    3.4 Data Adaptive Transform Models for OCT Denoising 50
    3.4.1 Conventional Dictionary Learning 50
    3.4.2 Dual Tree Complex Wavelet Transform 51
    3.4.3 Dictionary Learning with Wise Selection of Start Dictionary 52
    3.5 Non Data Adaptive Transform Models for OCT Denoising 56
    3.5.1 Denoising by Minimum Mean Square Error (MMSE) Estimator .58
    Chapter 4 Reconstruction of Retinal OCT Images with Sparse
    4.1 Introduction 75
    4.2 Sparse Representation for Image Reconstruction 77
    4.3 Sparsity Based on Methods for the OCT Image Reconstruction 78
    4.3.1 Multiscale Sparsity Based on Tomographic Denoising (MSBTD) 78
    4.3.2 Sparsity Based on Simultaneous Denoising and Interpolation
    (SBSDI) 86
    4.3.3 3D Adaptive Sparse Representation Based on Compression
    4.4 Conclusions 102
    References 104
    Chapter 5 Segmentation of OCT Scans Using Probabilistic Graphical
    5.1 Introduction 109
    5.2 A Probabilistic Graphical Model for Retina Segmentation 111
    5.2.1 The Graphical Model 111
    5.2.2 Variationallnference 114
    5.3 Results 117
    Contents v
    5.3.1 Segmentation Performance 117
    5.3.2 Pathology Detection 121
    5.4 Segmenting Pathological Scans 125
    5.5.1 Conclusion 127
    5.5.2 Prospective Work 127
    A Appendix 128
    A.l Derivation of the Objective (5.16) 128
    A.2 0ptimization with Respect to qb 132
    References 134
    Chapter 6 Diagnostic Capability of Optical Coherence Tomography Based
    Quantitative Analysis for Various Eye Diseases and
    Additional Factors Affecting Morphological
    6.1 Introduction 137
    6.2 0CT Based Retinal Morphological Measurements .140
    6.2.1 Quantitative Measurements of Retinal Morphology 140
    6.2.2 Quality, Artifacts, and Errors in Optical Coherence Tomography
    6.2.3 Effect of Axial Length on Thickness 144
    6.3 Capability of Optical Coherence Tomography Based Quantitative
    Analysis for Various Eye Diseases 147
    6.3.1 Diabetic Retinopathy 148
    6.3.2 Multiple Sclerosis 150
    6.3.3 Amblyopia 156
    6.4 Concluding Remarks 163
    References 165
    Chapter 7 Quantitative Analysis of Retinal Layers' Opticallntensities
    Based on Optical Coherence Tomography 182
    7.1 Introduction 182
    7.2 Automatic Layer Segmentation in OCT Images 184
    7.3 The Optical Intensity of Retinal Layers of Normal Subjects 185
    7.3.1 Data Acquisition 185
    7.3.2 Statistical Analysis 185
    7.3.3 Results of Quantitative Analysis of Retinal Layer Optical Intensities of
    Normal Subjects 185
    7.3.4 Discussion 188
    7.4 Distribution and Determinants of the Opticallntensity of Retinal Layers
    of Normal Subjects 188
    7.4.1 Data Acquisition and Image Processing 189
    7.4.2 Statistical Analysis 190
    7.4.3 Retinal Optical Intensity Measurement 190
    7.4.4 Determinants of Retinal Optical Intensity 194
    7.4.5 Discussion 195
    7.5 The Opticallntensity Distribution in Central Retinal Artery
    7.5.1 Central Retinal Artery Occlusion 195
    7.5.2 Subjects and Data Acquisition 196
    7.5.3 Image Analysis 197
    7.5.5 Discussion 200
    References 203
    Chapter 8 Segmentation of Optic Disc and Cup to Disc Ratio Quantification
    Based on OCT Scans 207
    8.1 Introduction 207
    8.2 0ptic Disc Segmentation 209
    8.2.1 0verview of the Method 210
    8.2.2 Coarse Disc Margin Location 211
    8.2.3 SVM Based Patch Searching 214
    8.3 Evaluation of Optic Disc Segmentation and C/D Ratio
    Quantification 216
    8.3.1 Evaluation of Optic Disc Segmentation 216
    8.3.2 Evaluation of C/D Ratio Quantification 219
    References 222
    Chapter 9 Choroidal OCT Analytics 225
    9.1 Introduction 225
    9.2 Automated Segmentation and High level Analytics 226
    9.2.1 Problem Setup and Solution Approaches 226
    9.2.2 Materials and Methods 228
    9.2.3 Results and Statistical Analysis 233
    9.3 Fine Grain Analysis 247
    9.3.1 Problem Setup and Solution Approaches 248
    9.3.3 Stromal Lumial Analysis: Experimental Results 252
    References 255
    Chapter 10 Layer Segmentation and Analysis for Retina with
    Diseases 259
    10.1 Intorduction 259
    10.2 Segmentation of Retinal Layers with Serous Pigment Epithelial
    Detachments 260
    10.2.3 Results 269
    10.3 Quantification of External Limiting Membrane Disruption Caused by
    Diabetic Macular Edema 275
    10.4 Detection of Photoreceptor Ellipsoid Zone Disruption Caused
    by Trauma 282
    10.4.3 Results 287
    10.5 Conclusions 292
    References 292
    Chapter 11 Segmentation and Visualization of Drusen and Geographic
    Atrophy in SD OCT Images 299
    11.1 Introduction 299
    11.1.2 Geographic Atrophy 301
    11.2 Drusen Segmentation and Visualization 301
    11.2.1 Automated Drusen Segmentation and Quantification in SD OCT
    11.2.2 An Improved OCT Derived Fundus Projectionlmage for Drusen
    11.3 Geographic Atrophy Segmentation and Visualization 323
    11.3.1 Semi Automatic Geographic Atrophy Segmentation for SD OCT
    11.3.2 Automated Geographic Atrophy Segmentation for SD OCT Images
    Using Region Based C V Model via Local Similarity Factor 330
    11.3.3 Restricted Summed Area Projection for Geographic Atrophy
    Visualization in SD OCT Images 340
    11.3.4 A False Color Fusion Strategy for Drusen and GA Visualization in
    OCTImages 348
    11.4 Conclusion 360
    References 360
    Chapter 12 Segmentation of Symptomatic Exudate Associated
    Derangements in 3D OCT Images 367
    12.1 Introduction 367
    12.2 Related Methods 369
    12.2.1 Conventional Graph Cut Algorithm 369
    12.2.2 0ptimal Surface Approach Graph Search Approach 369
    12.3 Probability Constrained Graph Search Graph Cut 369
    12.3.1 Initialization 370
    12.3.2 Graph Search Graph Cut SEAD Segmentation 373
    12.4 Performance Evaluation 377
    12.4.1 Experimental Methods 377
    12.4.2 Assessment of Initialization Performance 378
    12.4.3 Assessment of Segmentation Performance 379
    12.4.4 Statistical Correlation Analysis and Reproducibility Analysis 3 80
    12.5 Conclusion 381
    12.5.1 Importance of SEAD Segmentation 381
    12.5.2 Advantages of the Probability Constrained Graph Cut Graph Search
    12.5.3 Limitations of the Reported Method 383
    12.5.4 Segmentation of Abnormal Retinal Layers 384
    References 384
    Chapter 13 Modeling and Prediction of Choroidal Neovascularization
    Growth Based on Longitudinal OCT Scans 389
    13.1 Introduction 389
    13.2.1 Method Overview 391
    13.2.2 Data Acquisition 392
    13.2.3 Preprocessing 393
    13.2.4 Meshing 394
    13.2.5 CNV Growth Model 395
    13.2.6 Estimation of Growth Parameters 395
    13.3 Experimental Results 397
    13.4 Conclusions 399
    References 399
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