Artificial Intelligence in Digital Holographic Imaging
Technical Basis and Biomedical Applications
by Inkyu Moon
1st Edition
Publisher: Wiley-IEEE Press
Book Details
| Print ISBN | 9780470647509 |
| eText ISBN | 9781119239048 |
| Publisher | Wiley-IEEE Press |
| Publishing Year | 2023 |
| Edition | 1st Edition |
| Language | English |
Artificial Intelligence in Digital Holographic Imaging: Technical Basis and Biomedical Applications, 1st Edition, examines the integration of digital holography with artificial intelligence methods. The book outlines core principles and computational workflows for three-dimensional optical sensing, holographic imaging, analysis, and pattern recognition.
The volume explores how holographic microscopy investigates cell structure and dynamics with nanometric axial sensitivity to identify novel biomarkers. Key subjects include deep learning models for focus prediction, automated phase unwrapping, noise-free phase imaging, and label-free phenotypic screening to facilitate data-driven diagnosis.
Intended for readers of varied backgrounds, the text demonstrates how to incorporate machine learning algorithms into holographic system designs to address complex biomedical problems.
Table of Contents
Chapter 1: Introduction
Chapter 2: Coherent Optical Imaging
Chapter 3: Lateral and Depth Resolutions
Chapter 4: Phase Unwrapping
Chapter 5: Off-axis Digital Holographic Microscopy
Chapter 6: Gabor Digital Holographic Microscopy
Chapter 7: Introduction
Chapter 8: No-search Focus Prediction in DHM with Deep Learning
Chapter 9: Automated Phase Unwrapping in DHM with Deep Learning
Chapter 10: Noise-free Phase Imaging in Gabor DHM with Deep Learning
Chapter 11: Introduction
Chapter 12: Red Blood Cell Phase-image Segmentation
Chapter 13: Red Blood Cell Phase-image Segmentation with Deep Learning
Chapter 14: Automated Phenotypic Classification of Red Blood Cells
Chapter 15: Automated Analysis of Red Blood Cell Storage Lesions
Chapter 16: Automated Red Blood Cell Classification with Deep Learning
Chapter 17: High-throughput Label-free Cell Counting with Deep Neural Networks
Chapter 18: Automated Tracking of Temporal Displacements of Red Blood Cells
Chapter 19: Automated Quantitative Analysis of Red Blood Cell Dynamics
Chapter 20: Quantitative Analysis of Red Blood Cells during Temperature Elevation
Chapter 21: Automated Measurement of Cardiomyocyte Dynamics with DHM
Chapter 22: Automated Analysis of Cardiomyocytes with Deep Learning
Chapter 23: Automatic Quantification of Drug-treated Cardiomyocytes with DHM
Chapter 24: Analysis of Cardiomyocytes with Holographic Image-based Tracking
Chapter 25: Conclusion and Future Work
Customer Reviews
0.0
0 reviews
No reviews yet. Be the first to review this book!
Write a Review
Reviewed by GradeFocus Editorial Team
Related Books
Biomechanics of the Human Spine
Fabio Galbusera
Emerging Diagnostic Glucose Sensing Approaches
Abhishek Kandwal
Engineering Nanoparticles for Biomedical Applications
Sulalit Bandyopadhyay
Soft Electronics for Diagnosis, Therapy, and Integrated Systems
Xinge Yu
Green Carbon Dots for Theranostic Applications
Hamed Barabadi
Human-Machine interfaces in Medical Robotics
Yanpei Huang