Computational Optical Phase Imaging (Progress in Optical Science and Photonics, 21)

✍ Scribed by Cheng Liu, Shouyu Wang, Suhas P. Veetil

• Publisher: Springer
• Year: 2022
• Tongue: English
• Leaves: 311
• Category: Library

✦ Synopsis

In this book, computational optical phase imaging techniques are presented along with Matlab codes that allow the reader to run their own simulations and gain a thorough understanding of the current state-of-the-art. The book focuses on modern applications of computational optical phase imaging in engineering measurements and biomedical imaging. Additionally, it discusses the future of computational optical phase imaging, especially in terms of system miniaturization and deep learning-based phase retrieval.

✦ Table of Contents

Preface
Contents
1 Introduction to Computational Phase Imaging
1.1 Fundamentals of Optical Imaging
1.2 Limitations of Common Intensity Imaging
1.3 Intensity Imaging to Phase Imaging
1.4 Basic Principles of Computational Phase Imaging
References
2 Qualitative Phase Imaging
2.1 Phase Contrast Microscopy
2.2 Differential Interference Contrast (DIC) Microscopy
2.3 Spectrum Modulation Contrast Imaging
2.4 Hoffman Modulation Contrast Microscopy
2.5 Schlieren Photography
2.6 Comparison of Qualitative Phase Imaging Techniques
References
3 Interference-Based Quantitative Optical Phase Imaging
3.1 Description of Holography and Interferometry
3.2 Classification of Holography and Interferometry
3.2.1 On-Axis and Off-Axis
3.2.2 Fresnel and Fourier
3.2.3 Shearing and Non-shearing
3.3 Numerical Simulations on Holography and Interferometry
3.3.1 Numerical Simulation on Gabor Digital Holography
3.3.2 Numerical Simulation on On-Axis Digital Holography
3.3.3 Numerical Simulation on Off-Axis Digital Holography
3.3.4 Numerical Simulation on Interferometry
3.3.5 Numerical Simulation on Fresnel Digital Holography
3.3.6 Numerical Simulation on Fourier Digital Holography
3.3.7 Numerical Simulation on Lateral Shearing Interferometry
3.3.8 Numerical Simulation on Phase Unwrapping
3.4 Improvements in Holography and Interferometry
3.4.1 Improvements in Phase Retrieval Methods
3.5 Extensions on Holography and Interferometry
3.5.1 Spatial Light Interference Microscopy (SLIM)
3.5.2 Quantitative Differential Interference Contrast (DIC) Microscopy
3.5.3 Quadriwave Lateral Shearing Interferometry
3.5.4 Optical Scanning Holography (OSH)
3.5.5 Fresnel Incoherent Correlation Holography (FINCH)
3.5.6 Coded Aperture Correlation Holography (COACH)
3.5.7 Computer-Generated Holography (CGH)
3.6 Summary
References
4 Non-interferometric Quantitative Optical Phase Imaging
4.1 Coherent Diffraction Imaging
4.1.1 G-S Algorithm
4.1.2 ER and HIO Algorithms of Fienup
4.1.3 Existence of Convergence in Iterative CDI Algorithms
4.1.4 Equivalence of ER Algorithm and Steepest-Decent Method
4.1.5 Ptychographic Iterative Engine
4.1.6 Fourier Ptychographic Microscopy
4.1.7 Coherent Modulation Imaging
4.2 Transport of Intensity Equation Method
4.2.1 Theory of Transport of Intensity Equation and Its Classical Solution
4.2.2 Numerical Simulations on TIE Method
4.2.3 Important Improvements on Phase Retrieval
4.2.4 Important Improvement on Multi-focal Imaging
4.2.5 Discussion
4.3 Shack-Hartmann Wavefront Sensor
4.3.1 Theory of Hartmann and Shack-Hartmann Wavefront Sensors
4.3.2 Numerical Simulations on Shack-Hartmann Wavefront Sensor
4.3.3 Discussion
4.4 Other Quantitative Computational Optical Phase Imaging Techniques
4.4.1 Differential Phase Contrast Microscopy
4.4.2 Pyramid Wavefront Sensing
4.4.3 Moiré Deflectometry
4.4.4 Coded Aperture Phase Imaging
4.4.5 Phase Diversity
References
5 Typical Applications of Computational Phase Imaging
5.1 Measurement of Inner Stress and Deformation
5.1.1 Measurement of 3D Stress Around Laser Induced Damage
5.1.2 Measurement of Deformation with Digital Holography
5.2 Applications of CDI in Optical Engineering
5.2.1 Diagnosing the High Power Laser Beam Online with Coherent Modulation Imaging (CMI)
5.2.2 Inspection on the Quality of Optical Element with PIE
5.3 Computational Optical Phase Imaging in Biomedical Imaging
5.3.1 Computational Optical Phase Microscopy in Static Specimen Observation
5.3.2 Computational Optical Phase Imaging in Dynamic Specimen Observation
5.3.3 Computational Optical Phase Imaging in Hybrid Imaging
5.3.4 Computational Optical Phase Imaging in Extended Applications
5.3.5 Summary
5.4 Computational Optical Phase Imaging for Adaptive Optics
5.4.1 Computational Optical Phase Imaging in Optical Aberration Detection
5.4.2 Computational Optical Phase Imaging in Deep Imaging Within Complex Scattering Media
5.4.3 Summary
5.5 Refocusing and Tracking
5.5.1 Background
5.5.2 Refocusing in Optical Phase Imaging for In-Focus Image Reconstruction
5.5.3 Refocusing in Optical Phase Imaging for Depth of View Extension
5.5.4 Refocusing in Optical Phase Imaging for Three-Dimensional Particle Tracking
5.5.5 Summary
5.6 Three-Dimensional (3D) Computational Phase Imaging
5.6.1 Classical Optical Diffraction Tomography
5.6.2 3D Imaging with Curved Illumination
5.6.3 3D Imaging with K-Domain Transform
5.6.4 3D Imaging with Ptychography
5.7 Summary
References
6 Recent Trends in Computational Optical Phase Imaging
6.1 Deep Learning in Computational Optical Phase Imaging
6.1.1 Deep Learning Used in Phase Retrieval
6.1.2 Deep Learning Used in Computational Optical Phase Imaging Applications
6.1.3 Discussions
6.2 Point-of-Care Computational Optics Phase Imaging
6.2.1 Point-of-Care Digital Holographic Microscopy
6.2.2 Point-of-Care Ptychographic Microscopy
6.2.3 Point-of-Care Transport of Intensity Phase Microscopy
6.2.4 Point-of-Care Differential Phase Contrast Microscopy
6.2.5 Discussions
References