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Biomedical Texture Analysis
Fundamentals, Tools and Challenges
Teaches the fundamentals, advantages, pitfalls and challenges of biomedical texture analysis and how to apply them
Adrien Depeursinge (Edited by), Omar S Al-Kadi (Edited by), J.Ross Mitchell (Edited by)
9780128121337, Elsevier Science
Paperback, published 28 August 2017
430 pages
23.4 x 19 x 2.7 cm, 0.9 kg
Biomedical Texture Analysis: Fundamentals, Applications, Tools and Challenges describes the fundamentals and applications of biomedical texture analysis (BTA) for precision medicine. It defines what biomedical textures (BTs) are and why they require specific image analysis design approaches when compared to more classical computer vision applications. The fundamental properties of BTs are given to highlight key aspects of texture operator design, providing a foundation for biomedical engineers to build the next generation of biomedical texture operators. Examples of novel texture operators are described and their ability to characterize BTs are demonstrated in a variety of applications in radiology and digital histopathology. Recent open-source software frameworks which enable the extraction, exploration and analysis of 2D and 3D texture-based imaging biomarkers are also presented. This book provides a thorough background on texture analysis for graduate students and biomedical engineers from both industry and academia who have basic image processing knowledge. Medical doctors and biologists with no background in image processing will also find available methods and software tools for analyzing textures in medical images.
1. Fundamentals of Texture Processing for Biomedical Image Analysis 2. Multi-Scale and Multi-Directional Biomedical Texture Analysis 3. Biomedical Texture Operators and Aggregation Functions 4. Deep Learning in Texture Analysis and its Application to Tissue Image Classification 5. Fractals for Biomedical Texture Analysis 6. Handling of Feature Space Complexity for Texture Analysis in Medical Images 7. Rigid Motion Invariant Classification of 3D Textures 8. An Introduction to Radiomics: An Evolving Cornerstone of Precision Medicine 9. Deep Learning Techniques on Texture Analysis of Chest and Breast Images 10. Analysis of Histopathology Images 11. MaZda - a Framework for Biomedical Image Texture Analysis and Data Exploration 12. QuantImage - An Online Tool for High-Throughput 3D Radiomics Feature Extraction in PET-CT 13. Web-Based Tools for Exploring the Potential of Quantitative Imaging Biomarkers in Radiology
Subject Areas: Communications engineering / telecommunications [TJK], Electronics & communications engineering [TJ]