Biomedical Image Segmentation
eBook - PDF

Biomedical Image Segmentation

Advances and Trends

  1. 526 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Biomedical Image Segmentation

Advances and Trends

Book details
Table of contents
Citations

About This Book

As one of the most important tasks in biomedical imaging, image segmentation provides the foundation for quantitative reasoning and diagnostic techniques. A large variety of different imaging techniques, each with its own physical principle and characteristics (e.g., noise modeling), often requires modality-specific algorithmic treatment. In recent years, substantial progress has been made to biomedical image segmentation. Biomedical image segmentation is characterized by several specific factors. This book presents an overview of the advanced segmentation algorithms and their applications.

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Yes, you can access Biomedical Image Segmentation by Ayman El-Baz, Xiaoyi Jiang, Jasjit S. Suri in PDF and/or ePUB format, as well as other popular books in Medicine & Biotechnology in Medicine. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2016
ISBN
9781482258561

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Table of Contents
  6. Preface
  7. Editors
  8. Contributors
  9. Chapter 1: Deformable model-based methods for image segmentation
  10. Chapter 2: Domain knowledge for level set segmentation in medical imaging: A review
  11. Chapter 3: Robust image segmentation with a parametric deformable model using learned shape priors
  12. Chapter 4: A 3D active shape model for left ventricle segmentation in MRI
  13. Chapter 5: Model-based segmentation algorithms for myocardial magnetic resonance imaging sequences
  14. Chapter 6: Incorporating shape variability in implicit template deformation for image segmentation
  15. Chapter 7: Exudate detection in fundus images using active contour methods and region-wise classification
  16. Chapter 8: Preprocessing local features and fuzzy logic-based image segmentation
  17. Chapter 9: Model-based curvilinear network extraction toward quantitative microscopy
  18. Chapter 10: Level set-based cell segmentation using convex energy functionals
  19. Chapter 11: Histogram-based level set methods for medical image segmentation
  20. Chapter 12: An appearance-guided deformable model for 4D kidney segmentation using diffusion MRI
  21. Chapter 13: Prostate segmentation using deformable model-based methods: A review
  22. Chapter 14: A novel NMF-based CAD system for early diagnosis of prostate cancer by using 4D diffusion-weighted magnetic resonance images (DW-MRI)
  23. Chapter 15: Distance regularized level sets for segmentation of the left and right ventricles
  24. Chapter 16: Salient object segmentation with a shape-constrained level set
  25. Chapter 17: Tracking and segmentation of the endocardium of the left ventricle in a 2D ultrasound using deep learning architectures and Monte Carlo sampling
  26. Chapter 18: A shortest path approach to interactive medical image segmentation
  27. Chapter 19: Local statistical models for ultrasound image segmentation
  28. Chapter 20: Image segmentation with physical noise models
  29. Chapter 21: A fast lung segmentation approach
  30. Chapter 22: Fully automatic segmentation of hip CT images via landmark detection-based atlas selection and optimal surface detection
  31. Index