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Microscope Image Processing
- 2nd Edition - August 26, 2022
- Editors: Fatima Merchant, Kenneth Castleman
- Language: English
- Paperback ISBN:9 7 8 - 0 - 1 2 - 8 2 1 0 4 9 - 9
- eBook ISBN:9 7 8 - 0 - 1 2 - 8 2 1 0 5 0 - 5
Microscope Image Processing, Second Edition, introduces the basic fundamentals of image formation in microscopy including the importance of image digitization and display, which… Read more
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Request a sales quoteMicroscope Image Processing, Second Edition, introduces the basic fundamentals of image formation in microscopy including the importance of image digitization and display, which are key to quality visualization. Image processing and analysis are discussed in detail to provide readers with the tools necessary to improve the visual quality of images, and to extract quantitative information. Basic techniques such as image enhancement, filtering, segmentation, object measurement, and pattern recognition cover concepts integral to image processing. In addition, chapters on specific modern microscopy techniques such as fluorescence imaging, multispectral imaging, three-dimensional imaging and time-lapse imaging, introduce these key areas with emphasis on the differences among the various techniques.
The new edition discusses recent developments in microscopy such as light sheet microscopy, digital microscopy, whole slide imaging, and the use of deep learning techniques for image segmentation and analysis with big data image informatics and management.
Microscope Image Processing, Second Edition, is suitable for engineers, scientists, clinicians, post-graduate fellows and graduate students working in bioengineering, biomedical engineering, biology, medicine, chemistry, pharmacology and related fields, who use microscopes in their work and would like to understand the methodologies and capabilities of the latest digital image processing techniques or desire to develop their own image processing algorithms and software for specific applications.
The new edition discusses recent developments in microscopy such as light sheet microscopy, digital microscopy, whole slide imaging, and the use of deep learning techniques for image segmentation and analysis with big data image informatics and management.
Microscope Image Processing, Second Edition, is suitable for engineers, scientists, clinicians, post-graduate fellows and graduate students working in bioengineering, biomedical engineering, biology, medicine, chemistry, pharmacology and related fields, who use microscopes in their work and would like to understand the methodologies and capabilities of the latest digital image processing techniques or desire to develop their own image processing algorithms and software for specific applications.
- Presents a unique practical perspective of state-of-the-art microscope image processing and the development of specialized algorithms
- Each chapter includes in-depth analysis of methods coupled with the results of specific real-world experiments
- Co-edited by Kenneth R. Castleman, world-renowned pioneer in digital image processing and author of two seminal textbooks on the subject
Engineers, scientists, post-graduates and graduate students working in bioengineering, biomedical engineering, biology, medicine, chemistry, pharmacology and related fields
- Cover image
- Title page
- Table of Contents
- Copyright
- Foreword to the First Edition
- Reference
- Foreword to the Second Edition
- Preface to the First Edition
- Preface to the Second Edition
- Acknowledgments
- Chapter One: Introduction
- Abstract
- 1.1: The Microscope and Image Processing
- 1.2: The Scope of This Book
- 1.3: Our Approach
- 1.4: The Challenge
- 1.5: Modern Microscopy
- 1.6: Nomenclature
- 1.7: Summary of Important Points
- References
- Chapter Two: Fundamentals of Microscopy
- Abstract
- 2.1: The Origins of the Microscope
- 2.2: Optical Imaging
- 2.3: Diffraction Limited Optical Systems
- 2.4: Incoherent Illumination
- 2.5: Coherent Illumination
- 2.6: Resolution
- 2.7: Aberration
- 2.8: Calibration
- 2.9: Summary of Important Points
- References
- Chapter Three: Image Digitization and Display
- Abstract
- 3.1: Introduction
- 3.2: Digitizing Images
- 3.3: Overall System Design
- 3.4: Image Display
- 3.5: Summary of Important Points
- References
- Chapter Four: Geometric Transformations
- Abstract
- 4.1: Introduction
- 4.2: Implementation
- 4.3: Gray Level Interpolation
- 4.4: The Spatial Transformation
- 4.5: Applications
- 4.6: Summary of Important Points
- References
- Chapter Five: Image Enhancement
- Abstract
- 5.1: Introduction
- 5.2: Spatial Domain Enhancement Methods
- 5.3: Fourier Transform Methods
- 5.4: Wavelet Transform Methods
- 5.5: Color Image Enhancement
- 5.6: Summary of Important Points
- References
- Chapter Six: Morphological Image Processing
- Abstract
- 6.1: Introduction
- 6.2: Binary Morphology
- 6.3: Grayscale Operations
- 6.4: Watershed Segmentation
- 6.5: Summary of Important Points
- References
- Chapter Seven: Image Segmentation
- Abstract
- 7.1: Introduction
- 7.2: Region-Based Segmentation
- 7.3: Boundary-Based Segmentation
- 7.4: Summary of Important Points
- References
- Chapter Eight: Object Measurement
- Abstract
- 8.1: Introduction
- 8.2: Measures for Binary Objects
- 8.3: Distance Measures
- 8.4: Gray Level Object Measures
- 8.5: Object Measurement Considerations
- 8.6: Summary of Important Points
- References
- Chapter Nine: Object Classification
- Abstract
- 9.1: Introduction
- 9.2: The Classification Process
- 9.3: The Single-Feature, Two-Class Case
- 9.4: The Three-Feature, Three-Class Case
- 9.5: Classifier Performance
- 9.6: Bayes Risk
- 9.7: Relationships Among Bayes Classifiers
- 9.8: The Choice of a Classifier
- 9.9: Nonparametric Classifiers
- 9.10: Feature Selection
- 9.11: Neural Networks
- 9.12: Summary of Important Points
- References
- Chapter Ten: Multispectral Fluorescence Imaging
- Abstract
- 10.1: Introduction
- 10.2: Basics of Fluorescence Imaging
- 10.3: Optics in Fluorescence Imaging
- 10.4: Limitations in Fluorescence Imaging
- 10.5: Image Corrections in Fluorescence Microscopy
- 10.6: Quantifying Fluorescence
- 10.7: Fluorescence Imaging Techniques
- 10.8: Summary of Important Points
- References
- Chapter Eleven: Three-Dimensional Imaging
- Abstract
- 11.1: Introduction
- 11.2: Image Acquisition
- 11.3: 3D Image Data
- 11.4: Image Restoration and Deblurring
- 11.5: Image Fusion
- 11.6: Three-Dimensional Image Processing
- 11.7: Geometric Transformations
- 11.8: Pointwise Operations
- 11.9: Histogram Operations
- 11.10: Filtering
- 11.11: Morphological Operators
- 11.12: Segmentation
- 11.13: Comparing 3D Images
- 11.14: Registration
- 11.15: Object Measurements in 3D
- 11.16: 3D Image Display
- 11.17: Summary of Important Points
- References
- Chapter Twelve: Superresolution Image Processing
- Abstract
- 12.1: Introduction
- 12.2: The Diffraction Limit
- 12.3: Deconvolution
- 12.4: Superresolution Imaging Techniques
- 12.5: Summary of Important Points
- References
- Chapter Thirteen: Localization Microscopy
- Abstract
- 13.1: Introduction
- 13.2: Overcoming the Diffraction Limit
- 13.3: Localizing Molecular Position
- 13.4: Three-Dimensional Localization Microscopy
- 13.5: Quantitative Localization Microscopy
- 13.6: Implementation and Applications of SMLM
- 13.7: Summary of Important Points
- References
- Chapter Fourteen: Motion Tracking and Analysis
- Abstract
- 14.1: Introduction
- 14.2: Image Acquisition
- 14.3: Image Preprocessing
- 14.4: Image Analysis
- 14.5: Trajectory Analysis
- 14.6: Sample Algorithms
- 14.7: Summary of Important Points
- References
- Chapter Fifteen: Deep Learning
- Abstract
- 15.1: Introduction
- 15.2: Deep Learning Concepts
- 15.3: Practical Applications
- 15.4: Software Frameworks
- 15.5: Training Deep Learning Networks
- 15.6: Application of Deep Learning for Cell Nuclei Detection
- 15.7: Challenges
- 15.8: Summary of Important Points
- References
- Chapter Sixteen: Image Informatics
- Abstract
- 16.1: Introduction
- 16.2: Open-source Software Ecosystems
- 16.3: Image Acquisition
- 16.4: Image Storage and Curation
- 16.5: Visualization
- 16.6: Community
- 16.7: Conclusion
- 16.8: Summary of Important Points
- References
- Glossary
- Further reading
- Index
- No. of pages: 526
- Language: English
- Edition: 2
- Published: August 26, 2022
- Imprint: Academic Press
- Paperback ISBN: 9780128210499
- eBook ISBN: 9780128210505
FM
Fatima Merchant
Associate Professor Fatima Merchant works at Computer Engineering Technology and Computational Health Informatics in Houston, TX, USA.
Affiliations and expertise
Associate Professor, Computer Engineering Technology and Computational Health Informatics, Houston, TX, USAKC
Kenneth Castleman
Kenneth R. Castleman is the president of Advanced Digital Imaging Research (ADIR), the author of the canonical textbook Digital Image Processing ISBN 0-13-211467-4 and an authority in the field of image processing and pattern recognition. He holds a B.S, M.S. and Ph.D. all in electrical engineering from The University of Texas at Austin. In 1984, he co-founded Perceptive Systems, Inc (PSI) with Don Winkler in League City, TX.
Affiliations and expertise
President, Advanced Digital Imaging Research (ADIR), TX, USARead Microscope Image Processing on ScienceDirect