Handbook of Texture Analysis
eBook - ePub

Handbook of Texture Analysis

AI-Based Medical Imaging Applications

  1. 268 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Handbook of Texture Analysis

AI-Based Medical Imaging Applications

About this book

The major goals of texture research in computer vision are to understand, model, and process texture and, ultimately, to simulate the human visual learning process using computer technologies. In the last decade, artificial intelligence has been revolutionized by machine learning and big data approaches, outperforming human prediction on a wide range of problems. In particular, deep learning convolutional neural networks (CNNs) are particularly well suited to texture analysis. This volume presents important branches of texture analysis methods which find a proper application in AI-based medical image analysis. This book:

  • Discusses first-order, second-order statistical methods, local binary pattern (LBP) methods, and filter bank-based methods
  • Covers spatial frequency-based methods, Fourier analysis, Markov random fields, Gabor filters, and Hough transformation
  • Describes advanced textural methods based on DL as well as BD and advanced applications of texture to medial image segmentation
  • Is aimed at researchers, academics, and advanced students in biomedical engineering, image analysis, cognitive science, and computer science and engineering

This is an essential reference for those looking to advance their understanding in this applied and emergent field.

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Yes, you can access Handbook of Texture Analysis by Ayman El-Baz,Mohammed Ghazal,Jasjit S. Suri in PDF and/or ePUB format, as well as other popular books in Computer Science & Biomedical Science. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2024
Print ISBN
9780367483456
eBook ISBN
9781040008973
Edition
1
Topic
Computer Science
Subtopic
Biomedical Science
Index
Computer Science

Table of contents

  1. Cover
  2. Half Title
  3. Title
  4. Copyright
  5. Dedication
  6. Contents
  7. Preface
  8. List of Contributors
  9. Author Bios
  10. Acknowledgments
  11. Chapter 1 An Exploratory Review on Local Binary Descriptors for Texture Classification
  12. Chapter 2 Precision Grading of Glioma: A System for Accurate Diagnosis and Treatment Planning
  13. Chapter 3 Enhancing Accuracy in Liver Tumor Detection and Grading: A Computer-Aided Diagnostic System
  14. Chapter 4 Texture Analysis in Radiology
  15. Chapter 5 Texture Analysis Using a Self-Organizing Feature Map
  16. Chapter 6 Sensor-Based Human Activity Recognition Analysis Using Machine Learning and Topological Data Analysis (TDA)
  17. Chapter 7 Application of Texture Analysis in Retinal OCT Imaging
  18. Chapter 8 Automation in Pneumonia Detection
  19. Chapter 9 Texture for Neuroimaging
  20. Chapter 10 A Multimodal MR-Based CAD System for Precise Assessment of Prostatic Adenocarcinoma
  21. Chapter 11 Texture Analysis in Cancer Prognosis
  22. Index