| Description |
1 online resource (292 pages) |
| Contents |
Cover -- Title Page -- Copyright Page -- Contents -- Introduction -- Chapter 1. Quantitative Phase Microscopy Using Wavefront Analysis -- 1.1. Introduction -- 1.2. Description of the principles used in phase imaging -- 1.3. Quadriwave lateral shearing interferometry for high spatial resolution wavefront analysis -- 1.3.1. Generation of incident field replicas -- 1.3.2. Determination of the incident wavefront -- 1.3.3. Wavefront sensor implementation -- 1.4. Using a wavefront sensor in microscopy -- 1.4.1. Necessary approximations -- 1.4.2. Experimental configuration -- 1.5. Applications to biological imaging -- 1.5.1. High-contrast imaging without labeling -- 1.5.2. Dry mass measurement in living biological cells -- 1.5.3. Rapid imaging for biological phenomena -- 1.5.4. Quantitative phase and fluorescence correlative imaging -- 1.6. Optical retardance imaging -- 1.7. Other applications and new developments -- 1.8. References -- Chapter 2. Holography -- 2.1. Introduction -- 2.2. Principle of holography -- 2.3. Selection of the +1 order -- 2.3.1. Off-axis holography -- 2.3.2. Phase-shifting holography -- 2.4. Holographic reconstruction -- 2.4.1. Fourier transform reconstruction -- 2.4.2. Two Fourier transform reconstruction (angular spectrum) -- 2.4.3. Two Fourier transform reconstruction with zero padding -- 2.4.4. Two Fourier transform reconstruction with the addition of a digital lens -- 2.5. Associated holographic configurations and applications -- 2.5.1. In-line holography -- 2.5.2. Off-axis holography -- 2.5.3. Holographic microscopy and quantitative phase imaging -- 2.6. Conclusion -- 2.7. References -- Chapter 3. Inverse Problems for Image Reconstruction in Holography -- 3.1. Introduction -- 3.1.1. Notations -- 3.2. Direct model -- 3.3. Experimental application -- 3.4. Maximum likelihood approach -- 3.4.1. Formal expression |
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3.4.2. Noise statistics and likelihood -- 3.4.3. Backpropagation -- 3.4.4. Iterative methods for maximum likelihood estimation -- 3.4.5. Extrapolation of the field of view -- 3.5. Phase reconstruction: a nonlinear problem -- 3.6. Alternating projection methods -- 3.6.1. From alternating projection to criterion minimization -- 3.6.2. Maximum likelihood approach -- 3.7. Improving over the maximum likelihood -- 3.7.1. Penalized maximum likelihood -- 3.7.2. Bayesian interpretation: maximum a posteriori -- 3.8. Regularization functions and a priori -- 3.8.1. Quadratic regularization -- 3.8.2. Edge-preserving smoothing -- 3.8.3. Sparsity -- 3.8.4. Joint parsimony -- 3.8.5. Total variation -- 3.8.6. Plug and play regularization -- 3.9. Choosing the optimization algorithm for the solution of the inverse problem -- 3.10. Practical examples -- 3.10.1. Unconstrained and differentiable problem -- 3.10.2. Constrained problems -- 3.11. References -- Chapter 4. In-line Digital Holographic Microscopy Sample Reconstruction -- 4.1. Introduction -- 4.2. From classical microscopy to digital holography in the biomedical field -- 4.3. In-line holographic microscopy setups -- 4.3.1. Imaging setup, with or without lens -- 4.3.2. Coherence and illumination setup -- 4.4. Typical IP methodology for in-line hologram reconstruction -- 4.4.1. Test case: in-line holograms of micrometric transparent objects -- 4.4.2. In-line hologram formation model -- 4.4.3. Digital reconstructions -- 4.5. Extended contribution of IP approaches: digital super-resolution and field extension -- 4.5.1. Direct problem -- 4.5.2. Criterion to be minimized -- 4.5.3. Alternating reconstruction algorithm -- 4.6. Going further -- 4.6.1. Model refinement and self-calibration -- 4.6.2. Multivariate data reconstruction -- 4.6.3. Toward 3D reconstruction -- 4.7. References |
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Chapter 5. Transmission Tomographic Diffractive Microscopy -- 5.1. Introduction -- 5.2. Holographic microscopy: utility and limitations -- 5.3. Link between diffracted field and index distribution -- 5.3.1. Principle -- 5.3.2. Helmholtz equation in a weakly inhomogeneous medium -- 5.3.3. Born approximation -- 5.3.4. Spectral support in 3D Fourier space -- 5.3.5. Holographic algorithm -- 5.4. From holography to tomography -- 5.4.1. Illumination rotation -- 5.4.2. Sample rotation -- 5.4.3. Sample and illumination rotation -- 5.5. Practical implementations -- 5.5.1. Sample rotation techniques -- 5.5.2. Scanning illumination techniques -- 5.6. Reconstruction under the Born hypothesis -- 5.6.1. Examples of commercial systems -- 5.7. Conclusion -- 5.8. References -- Chapter 6. Interference Microscopy -- 6.1. Introduction -- 6.2. Principle and theory -- 6.2.1. Interference -- 6.2.2. Coherence of light -- 6.3. Algorithms -- 6.3.1. Phase-shifting microscopy -- 6.3.2. Coherence scanning interferometry -- 6.4. Instrumentation -- 6.5. Physical performance and limitations -- 6.5.1. Lateral resolution -- 6.5.2. Axial resolution -- 6.5.3. Spatial sampling -- 6.5.4. Sources of measurement error -- 6.6. Applications -- 6.6.1. Roughness measurement -- 6.6.2. The measurement of static surfaces -- 6.6.3. The measurement of moving surfaces -- 6.7. Recent findings -- 6.7.1. Full-field optical coherence tomography -- 6.7.2. Local spectroscopy -- 6.7.3. Microsphere-assisted microscopic interferometry -- 6.8. Conclusion -- 6.9. Acknowledgments -- 6.10. References -- Chapter 7. Multimodal and Multispectral Endoscopic Imaging with Extended Field of View -- 7.1. Introduction to conventional endoscopy -- 7.1.1. Principle and medical applications of endoscopy -- 7.1.2. Relevance and limitations of conventional endoscopy -- 7.1.3. Chapter objectives and content |
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7.2. The functioning of endoscopes -- 7.2.1. Components of an endoscopic system -- 7.2.2. Pinhole camera model -- 7.2.3. Distortion modeling and correction -- 7.2.4. Vignetting modeling and correction -- 7.3. 3D cartography of endoscopic scenes -- 7.3.1. Data registration from two viewpoints -- 7.3.2. 3D cartography approaches -- 7.4. Multimodal and multispectral endoscopic imaging systems -- 7.4.1. Introduction -- 7.4.2. Chemical labeling imaging systems -- 7.4.3. Exogenous markerless imaging systems -- 7.5. Conclusion -- 7.6. References -- Chapter 8. An Introduction to Single-Pixel Imaging -- 8.1. Introduction -- 8.1.1. Mathematical formulation -- 8.1.2. Experimental implementation -- 8.2. Hadamard transform optics: the origins (1970-1980) -- 8.3. Compressed sensing: the revival (2006-2016) -- 8.3.1. Undersampled acquisition -- 8.3.2. Compressed sensing general principle -- 8.3.3. Choice of acquisition patterns -- 8.4. Deep learning reconstruction -- 8.4.1. General principle -- 8.4.2. Model architecture -- 8.4.3. Training -- 8.4.4. Simple link with conventional methods -- 8.4.5. Best linear estimator: Bayesian completion -- 8.4.6. Taking noise into consideration -- 8.5. Conclusion -- 8.6. Acknowledgments -- 8.7. References -- Glossary -- List of Authors -- Index -- EULA |
| Summary |
This book, coordinated by Corinne Fournier and Olivier Haeberlé, provides a comprehensive exploration of optical imaging technologies and their applications in biological sciences. It covers advanced topics such as quantitative phase microscopy, holography, and inverse problem-solving in imaging. The book is structured to guide readers through the principles and techniques used in phase imaging, holographic configurations, and the application of these technologies in biological research, including high-contrast imaging and dry mass measurement in living cells. Aimed at researchers and professionals in biology and optical imaging, this work offers insights into the latest developments and practical applications of optical imaging techniques. Generated by AI |
| Notes |
Description based on publisher supplied metadata and other sources |
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Part of the metadata in this record was created by AI, based on the text of the resource |
| Subject |
Optical images. Generated by AI
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Holography. Generated by AI
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| Form |
Electronic book
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| Author |
Haeberle, Olivier
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| ISBN |
9781394283996 |
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1394283997 |
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9781394283972 |
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1394283970 |
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