The BIOMEDICAL ENGINEERING Series Series Editor Michael R. Neuman. Uriiwsity of Calßy ülgaiy, Nbeitai, Cart. (g) CRC PRESS
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1 The BIOMEDICAL ENGINEERING Series Series Editor Michael R. Neuman Biomedical Image Analysis Uriiwsity of Calßy ülgaiy, Nbeitai, Cart (g) CRC PRESS Boca Raton London New York Washington, D.C.
2 Contents Preface About the Author Acknowledgments Symbols and Abbreviations vii xiii xv xxix 1 The Nature of Biomedical Images Body Temperature as an Image Transillumination Light Microscopy Electron Microscopy X-ray Imaging Breast Cancer and mammography Tomography Nuclear Medicine Imaging Ultrasonography Magnetic Resonance Imaging Objectives of Biomedical Image Analysis Computer-aided Diagnosis Remarks Study Questions and Problems Laboratory Exercises and Projects 58 2 Image Quality and Information Content Difficulties in Image Acquisition and Analysis Characterization of Image Quality Digitization of Images Sampling Quantization Array and matrix representation of images Optical Density Dynamic Range Contrast Histogram Entropy Blur and Spread Functions Resolution 99
3 XX Biomedical Image Analysis 2.11 The Fourier Transform and Spectral Content Important properties of the Fourier transform Modulation Transfer Function Signal-to-Noise Ratio Error-based Measures Application: Image Sharpness and Acutance Remarks Study Questions and Problems Laboratory Exercises and Projects 149 Removal of Artifacts Characterization of Artifacts Random noise Examples of noise PDFs Structured noise Physiological interference Other types of noise and artifact Stationary versus nonstationary processes Covariance and cross-correlation Signal-dependent noise Synchronized or Multiframe Averaging Space-domain Local-statistics-based Filters The mean filter The median filter Order-statistic alters Frequency-domain Filters Removal of high-frequency noise Removal of periodic artifacts Matrix Representation of Image Processing Matrix representation of images Matrix representation of transforms Matrix representation of convolution Illustrations of convolution Diagonalization of a circulant matrix Block-circulant matrix representation of a 2D filter Optimal Filtering The Wiener filter Adaptive Filters The local LMMSE filter The noise-updating repeated Wiener filter The adaptive 2D LMS filter The adaptive rectangular window LMS filter The adaptive-neighborhood filter Comparative Analysis of Filters for Noise Removal Application: Multiframe Averaging in Confocal Microscopy. 270
4 Table of Contents xxi 3.10 Application: Noise Reduction in Nuclear Medicine Imaging Remarks Study Questions and Problems Laboratory Exercises and Projects Image Enhancement Digital Subtraction Angiography Dual-energy and Energy-subtraction X-ray Imaging Temporal Subtraction Gray-scale Transforms Gray-scale thresholding Gray-scale windowing Gamma correction Histogram Transformation Histogram equalization Histogram specification Limitations of global Operations Local-area histogram equalization Adaptive-neighborhood histogram equalization Convolution Mask Operators Unsharp masking Subtracting Laplacian Limitations of fixed Operators High-frequency Emphasis Homomorphic Filtering for Enhancement Generalized linear filtering Adaptive Contrast Enhancement Adaptive-neighborhood contrast enhancement Objective Assessment of Contrast Enhancement Application: Contrast Enhancement of Mammograms Clinical evaluation of contrast enhancement Remarks Study Questions and Problems Laboratory Exercises and Projects Detection of Regions of Interest Thresholding and Binarization Detection of Isolated Points and Lines Edge Detection Convolution mask Operators for edge detection The Laplacian of Gaussian Scale-space methods for multiscale edge detection Canny's method for edge detection Fourier-domain methods for edge detection Edge linking 392
5 xxii Biomedical Image Analysis 5.4 Segmentation and Region Growing Optimal thresholding Region-oriented segmentation of images Splitting and merging of regions Region growing using an additive tolerance Region growing using a multiplicative tolerance Analysis of region growing in the presence of noise Iterative region growing with multiplicative tolerance Region growing based upon the human visual System Application: Detection of calcifications by multitolerance region growing Application: Detection of calcifications by linear prediction error Fuzzy-set-based Region Growing to Detect Breast Tumors Preprocessing based upon fuzzy sets Fuzzy segmentation based upon region growing Fuzzy region growing Detection of Objects of Known Geometry The Hough transform Detection of straight lines Detection of circles Methods for the Improvement of Contour or Region Estimates Application: Detection of the Spinal Canal Application: Detection of the Breast Boundary in Mammograms Detection using the traditional active deformable contour model Adaptive active deformable contour model Results of application to mammograms Application: Detection of the Pectoral Muscle in Mammograms Detection using the Hough transform Detection using Gabor wavelets Results of application to mammograms Application: Improved Segmentation of Breast Masses by Fuzzy-set-based Fusion of Contours and Regions Remarks Study Questions and Problems Laboratory Exercises and Projects Analysis of Shape Representation of Shapes and Contours Signatures of contours Chain coding Segmentation of contours 534
6 Table of Contents xxiii Polygonal modeling of contours Parabolic modeling of contours Thinning and skeletonization Shape Factors Compactness Moments Chord-length statistics Fourier Descriptors Fractional Concavity Analysis of Spicularity Application: Shape Analysis of Calcifications Application: Shape Analysis of Breast Masses and Tumors Remarks Study Questions and Problems Laboratory Exercises and Projects 582 Analysis of Texture Texture in Biomedical Images Models for the Generation of Texture Random texture Ordered texture Oriented texture Statistical Analysis of Texture The gray-level co-occurrence matrix Haralick's measures of texture Laws' Measures of Texture Energy Fractal Analysis Fractal dimension Fractional Brownian motion model Fractal analysis of texture Applications of fractal analysis Fourier-domain Analysis of Texture Segmentation and Structural Analysis of Texture Homomorphic deconvolution of periodic patterns Audification and Sonification of Texture in Images Application: Analysis of Breast Masses Using Texture and Gradient Measures Adaptive normals and ribbons around mass margins Gradient and contrast measures Results of pattern Classification Remarks Study Questions and Problems Laboratory Exercises and Projects 638
7 xxiv Biornedical Image Analysis 8 Analysis of Oriented Patterns Oriented Patterns in Images Measures of Directional Distribution The rose diagram The principal axis Angular moments Distance measures Entropy Directional Filtering Sector filtering in the Fourier domain Thresholding of the component images Design of fan Alters Gabor Filters Multiresolution signal decomposition Formation of the Gabor filter bank Reconstruction of the Gabor filter bank Output Directional Analysis via Multiscale Edge Detection Hough-Radon Transform Analysis Limitations of the Hough transform The Hough and Radon transforms combined Filtering and integrating the Hough-Radon space Application: Analysis of Ligament Healing Analysis of Collagen remodeling Analysis of the microvascular structure Application: Detection of Breast Tumors Framework for pyramidal decomposition Segmentation based upon density slicing Hierarchical grouping of isointensity contours Results of segmentation of masses Detection of masses in füll mammograms Analysis of mammograms using texture flow-field Adaptive computation of features in ribbons Results of mass detection in füll mammograms Application: Bilateral Asymmetry in Mammograms The fibroglandular disc Gaussian mixture model of breast density Delimitation of the fibroglandular disc Motivation for directional analysis of mammograms Directional analysis of fibroglandular tissue Characterization of bilateral asymmetry Application: Architectural Distortion in Mammograms Detection of spiculated lesions and distortion Phase portraits Estimating the orientation field Characterizing orientation fields with phase portraits 782
8 Table of Contents xxv Feature extraction for pattern Classification Application to Segments of mammograms Detection of sites of architectural distortion Remarks Study Questions and Problems Laboratory Exercises and Projects Image Reconstruction from Projections Projection Geometry The Fourier Slice Theorem Backprojection Filtered backprojection Discrete filtered backprojection Algebraic Reconstruction Techniques Approximations to the Kaczmarz method Imaging with Diffracting Sources Display of CT Images Agricultural and Forestry Applications Microtomography Application: Analysis of the Tumor in Neuroblastoma Neuroblastoma Tissue characterization using CT Estimation of tissue composition from CT images Results of application to clinical cases Discussion Remarks Study Questions and Problems Laboratory Exercises and Projects Deconvolution, Deblurring, and Restoration Linear Space-invariant Restoration Filters Inverse filtering Power spectrum equalization The Wiener filter Constrained least-squares restoration The Metz filter Information required for image restoration Motion deblurring Blind Deblurring Iterative blind deblurring Homomorphic Deconvolution The complex cepstrum Echo removal by Radon-domain cepstral filtering Space-variant Restoration Sectioned image restoration 893
9 XXVI Biomedical Image Analysis Adaptive-neighborhood deblurring The Kaiman filter Application: Restoration of Nuclear Medicine Images Quality control Scatter compensation Attenuation correction Resolution recovery Geometrie averaging of conjugate projeetions Examples of restoration of SPECT images Remarks Study Questions and Problems Laboratory Exercises and Projects Image Coding and Data Compression Considerations Based on Information Theory Noiseless coding theorem for binary transmission Lossy versus lossless compression Distortion measures and fidelity criteria Fundamental Concepts of Coding Direct Source Coding Huffman coding Run-length coding Arithmetic coding Lempel-Ziv coding Contour coding Application: Source Coding of Digitized Mammograms The Need for Decorrelation Transform Coding The discrete cosine transform The Karhunen-Loeve transform Encoding of transform coefficients Interpolative Coding Predictive Coding Two-dimensional linear prediction Multichannel linear prediction Adaptive 2D recursive least-squares prediction Image Scanning Using the Peano-Hilbert Curve Definition of the Peano-scan path Properties of the Peano-Hilbert curve Implementation of Peano scanning Decorrelation of Peano-scanned data Image Coding and Compression Standards The JBIG Standard The JPEG Standard The MPEG Standard 1050
10 Table of Contents xxvii The ACR/ NEMA and DICOM Standards Segmentation-based Adaptive Scanning Segmentation-based coding Region-growing criteria The SLIC procedure Results of image data compression with SLIC Enhanced JBIG Coding Lower-limit Analysis of Lossless Data Compression Memoryless entropy Markov entropy Estimation of the true source entropy Application: Teleradiology Analog teleradiology Digital teleradiology High-resolution digital teleradiology Remarks Study Questions and Problems Laboratory Exercises and Projects Pattern Classification and Diagnostic Decision Pattern Classification Supervised Pattern Classification Discriminant and decision functions Distance functions The nearest-neighbor rule Unsupervised Pattern Classification Cluster-seeking methods Probabilistic Models and Statistical Decision Likelihood functions and Statistical decision Bayes classifier for normal patterns Logistic Regression The Training and Test Steps The leave-one-out method Neural Networks Measures of Diagnostic Accuracy Receiver operating characteristics McNemar's test of symmetry Reliability of Features, Classifiers, and Decisions Statistical separability and feature selection Application: Image Enhancement for Breast Cancer Screening Case selection, digitization, and presentation ROC and Statistical analysis Discussion 1159
11 xxviii Biomedical Image Analysis Application: Classification of Breast Masses and Tumors via Shape Analysis Application: Content-based Retrieval and Analysis of Breast Masses Pattern Classification of masses Content-based retrieval Extension to telemedicine Remarks Study Questions and Problems Laboratory Exercises and Projects 1185 References 1187 Index 1262
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