Despeckle Filtering Algorithms and Software for Ultrasound Imaging

Book description

It is well-known that speckle is a multiplicative noise that degrades image quality and the visual evaluation in ultrasound imaging. This necessitates the need for robust despeckling techniques for both routine clinical practice and teleconsultation. The goal for this book is to introduce the theoretical background (equations), the algorithmic steps, and the MATLAB™ code for the following group of despeckle filters: linear filtering, nonlinear filtering, anisotropic diffusion filtering and wavelet filtering. The book proposes a comparative evaluation framework of these despeckle filters based on texture analysis, image quality evaluation metrics, and visual evaluation by medical experts, in the assessment of cardiovascular ultrasound images recorded from the carotid artery. The results of our work presented in this book, suggest that the linear local statistics filter DsFlsmv, gave the best performance, followed by the nonlinear geometric filter DsFgf4d, and the linear homogeneous mask area filter DsFlsminsc. These filters improved the class separation between the asymptomatic and the symptomatic classes (of ultrasound images recorded from the carotid artery for the assessment of stroke) based on the statistics of the extracted texture features, gave only a marginal improvement in the classification success rate, and improved the visual assessment carried out by two medical experts. A despeckle filtering analysis and evaluation framework is proposed for selecting the most appropriate filter or filters for the images under investigation. These filters can be further developed and evaluated at a larger scale and in clinical practice in the automated image and video segmentation, texture analysis, and classification not only for medical ultrasound but for other modalities as well, such as synthetic aperture radar (SAR) images. Table of Contents: Introduction to Ultrasound Imaging / Despeckle Filtering Algorithms / Evaluation Methodology / Applications of Despeckle Filtering in Ultrasound Imaging / Comparison and Discussion of Despeckle Filtering Algorithms / Summary and Future Directions

Table of contents

  1. Despeckle Filtering Algorithms and Software for Ultrasound Imaging
    1. Abstract
    2. Keywords
    3. Dedication
    4. Preface
    5. Acknowledgments
    6. Contents
    7. chapter 1
      1. Introduction to Ultrasound Imaging and Speckle Noise
        1. 1.1 A BRIEF REVIEW OF ULTRASOUND IMAGING
          1. 1.1.1 Basic Principles of Ultrasound Imaging
          2. 1.1.2 Ultrasound Modes
          3. 1.1.3 Image Quality and Resolution
          4. 1.1.4 Limitations of Ultrasound Imaging
        2. 1.2 SPECKLE NOISE
          1. 1.2.1 Physical Properties and the Pattern of Speckle Noise
          2. 1.2.2 Speckle Noise Modeling
          3. 1.2.3 Early Attempts of Despeckle Filtering in Different Modalities and Ultrasound Imaging
        3. 1.3 AN OVERVIEW OF DESPECKLE FILTERING TECHNIQUES
        4. 1.4 LIMITATIONS OF DESPECKLE FILTERING TECHNIQUES
        5. 1.5 GUIDE TO BOOK CONTENTS
    8. chapter 2
      1. Despeckle Filtering Algorithms
        1. 2.1 LINEAR FILTERING
          1. 2.1.1 First-Order Statistics Filtering (DsFlsmv and DsFwiener)
          2. 2.1.2 Local Statistics Filtering with Higher Moments (DsFlsminv1d and DsFlsmvsk2d)
          3. 2.1.3 Homogeneous Mask Area Filtering (DsFlsminsc)
        2. 2.2 NONLINEAR FILTERING
          1. 2.2.1 Median Filtering (DsFmedian)
          2. 2.2.2 Linear Scaling Filter (DsFca, DsFlecasort, and DsFls)
          3. 2.2.3 Maximum Homogeneity Over Pixel Neighborhood Filtering (DsFhomog)
          4. 2.2.4 Geometric Filtering (DsFgf4d)
          5. 2.2.5 Homomorphic Filtering (DsFhomo)
        3. 2.3 DIFFUSION FILTERING
          1. 2.3.1 Anisotropic Diffusion Filtering (DsFad)
          2. 2.3.2 Speckle-Reducing Anisotropic Diffusion Filtering (DsFsrad)
          3. 2.3.3 Coherent Nonlinear Anisotropic Diffusion Filtering (DsFnldif)
        4. 2.4 WAVELET FILTERING (DsFwaveltc)
    9. chapter 3
      1. Evaluation Methodology
        1. 3.1 MATERIAL AND RECORDING OF ULTRASOUND IMAGES
        2. 3.2 USE OF PHANTOM AND ARTIFICIAL ULTRASOUND IMAGES
          1. 3.2.1 Types of Plaques
        3. 3.3 IMAGE NORMALIZATION
        4. 3.4 DESPECKLE FILTERING
        5. 3.5 TEXTURE ANALYSIS
        6. 3.6 DISTANCE MEASURES
        7. 3.7 UNIVARIATE STATISTICAL ANALYSIS
        8. 3.8 kNN CLASSIFIER
        9. 3.9 IMAGE QUALITY EVALUATION METRICS
        10. 3.10 VISUAL EVALUATION BY EXPERTS
    10. chapter 4
      1. Applications of Despeckle Filtering in Ultrasound Imaging
        1. 4.1 EVALUATION OF DESPECKLE FILTERING ON PHANTOM AND ARTIFICIAL IMAGES
          1. 4.1.1 Phantom Image
          2. 4.1.2 Artificial Carotid Image
          3. 4.1.3 Real Carotid Ultrasound Image
          4. 4.1.4 Real Cardiac Ultrasound Images
        2. 4.2 EVALUATION OF DESPECKLE FILTERING ON CAROTID PLAQUE IMAGES BASED ON TEXTURE ANALYSIS
          1. 4.2.1 Distance Measures
          2. 4.2.2 Univariate Statistical Analysis
          3. 4.2.3 kNN Classifier
        3. 4.3 IMAGE QUALITY AND VISUAL EVALUATION
        4. 4.4 SEGMENTATION OF THE INTIMA-MEDIA COMPLEX AND PLAQUE IN THE CCA BASED ON DESPECKLE FILTERING
          1. 4.4.1 Intima-Media Complex and Plaque Segmentation
          2. 4.4.2 Video Despeckling
        5. 4.5 EVALUATION OF TWO DIFFERENT ULTRASOUND SCANNERS BASED ON DESPECKLE FILTERING
          1. 4.5.1 Evaluation of Despeckle Filtering on an Ultrasound Image
          2. 4.5.2 Evaluation of Despeckle Filtering on Gray-value Line Profiles
          3. 4.5.3 Evaluation of Despeckle Filtering Based on Visual Perception Evaluation
          4. 4.5.4 Evaluation of Despeckle Filtering based on Statistical and Texture Features
          5. 4.5.5 Evaluation of Despeckle Filtering Based on Image Quality Evaluation Metrics
    11. chapter 5
      1. Comparison and Discussion of Despeckle Filtering Algorithms
        1. 5.1 COMPARISON AND DISCUSSION OF DESPECKLE FILTERING ALGORITHMS
        2. 5.2 DESPECKLE FILTERING OF CAROTID PLAQUE IMAGES BASED ON TEXTURE ANALYSIS
        3. 5.3 DESPECKLING OF THE INTIMA-MEDIA COMPLEX AND THE PLAQUE
        4. 5.4 VIDEO DESPECKLING
          1. 5.4.1 Discussion
        5. 5.5 IMAGE QUALITY AND VISUAL EVALUATION
        6. 5.6 VISUAL PERCEPTION AND ADDITIONAL COMMENTS BY EXPERTS
        7. 5.7 SUMMARY FINDINGS ON DESPECKLE FILTERING
    12. chapter 6
      1. Summary and Future Directions
        1. 6.1 SUMMARY
        2. 6.2 FUTURE DIRECTIONS
    13. Appendices (1/2)
    14. Appendices (2/2)
    15. List of Symbols
    16. List of Abbreviations
    17. References (1/2)
    18. References (2/2)
    19. Author Biography

Product information

  • Title: Despeckle Filtering Algorithms and Software for Ultrasound Imaging
  • Author(s): Constantinos Pattichis, Christos Loizou
  • Release date: September 2008
  • Publisher(s): Morgan & Claypool Publishers
  • ISBN: 9781598296211