Advanced Photonics Methods for Biomedical Applications

Description

Advanced photonics methods for biomedical applications give researchers in universities and industries, and clinicians an overview of the novel tools for cancer diagnostics and treatment. This book provides researchers and professionals in the area of biomedical photonics with a toolbox of novel methodologies for biomedical applications, including health diagnostics, cancer detection, and treatment. It covers the theory, modeling, and design of each method, alongside their applications, fabrication, characterization, and measurements in clinical practice. A wide scope of concepts concerning innovative science and technologies of medicine will be covered, providing the readers with the latest research, developments, and technologies. It will also be a valuable resource for students and early-career researchers, alongside those involved in the design of the novel photonics-based techniques for health diagnostics and cancer detection and treatment. Key features • Discusses novel methods of cancer diagnostics and cancer treatment. • Details non and minimally invasive photonics techniques. • Explores the applications of machine learning and artificial intelligence to these novel techniques. Cover Half Title Title Page Copyright Page Table of Contents Contributors Chapter 1 In Vivo Fluorescence Measurements of Biological Tissue Viability 1.1 Introduction 1.2 Individual Variability of Measured Parameters 1.2.1 The Study of the Effect of Melanin on Recorded Signals 1.2.2 Effect of Blood Filling of Biological Tissue on the Recorded Signals 1.3 In Vivo Fluorescence Diagnostics 1.3.1 Application of Fluorescence Spectroscopy to Assess Tissue Viability in Feet of Patients with Diabetes Mellitus 1.3.2 The Study of Epithelial Tissue Fluorescence in the Example of the Bladder Cancer 1.4 Fluorescence Phantoms 1.4.1 FAD Fluorescence Phantom 1.4.2 Riboflavin and PPIX Fluorescence Phantom 1.5 Summary Acknowledgments References Chapter 2 The Discrete Analysis of the Tissue Biopsy Images with Metamaterial Formalisation 2.1 Introduction 2.2 Theoretical Background 2.3 Modelling of the Phantom Tissue 2.4 MMF Approach 2.4.1 Digitizeit Software 2.4.2 Calculation of the Effective Permittivity of the Disordered Metamaterial Model 2.5 Investigation of the Mouse Brain Tissue Samples by Means of MMF Approach 2.6 Investigation of the Liver Samples by Means of MMF Approach 2.6.1 Dataset Composition 2.6.2 K-Means Clustering 2.6.3 Differential Evolution Algorithm 2.7 CNN-Based Analysis of Liver Biopsy Images after Application of MMF 2.8 Conclusions References Chapter 3 Biomedical Applications of Terahertz Radiation 3.1 Introduction 3.2 Terahertz Spectroscopic and Imaging Systems 3.2.1 Pulsed THz Components and Setups 3.2.1.1 Photoconductive Antennas and Principles of THz Time-Domain Spectroscopy 3.2.1.2 Nonlinear Crystals and Laser Filaments as THz Sources 3.2.1.3 Spintronic Emitters 3.2.1.4 Setups for Pulsed THz Spectroscopy and Imaging 3.2.1.5 Terahertz Pulse Time-Domain Holography 3.2.2 CW Terahertz Components and Setups 3.2.2.1 CW Terahertz Imaging 3.3 THz Studies of the Skin 3.3.1 Skin Burns and Bruises Monitoring 3.3.2 Drug Delivery through Skin Monitoring 3.3.3 Skin Hydration Monitoring 3.3.3.1 Monitoring the Diabetes 3.3.4 Reading Fingerprints with THz Radiation 3.4 Cancer Cell Detection by THz Radiation 3.4.1 Skin Cancer 3.4.2 Breast Cancer 3.4.3 Brain Cancer 3.4.4 Other Cancers 3.4.4.1 Colorectal Cancer 3.4.4.2 Cervical Cancer 3.4.4.3 Liver Cancer 3.4.4.4 Tongue Cancer 3.4.4.5 Lung Cancer 3.4.4.6 Gastric Cancer 3.4.4.7 Ovarian Cancer 3.4.4.8 Prostate Cancer 3.5 Other Biomedical Applications of THz Spectroscopy and Imaging 3.5.1 Ophthalmologic Applications of THz Radiation 3.5.2 Stomatologic Applications of THz Radiation 3.5.3 Hematologic Applications of THz Radiation 3.5.4 Tissue Studies 3.5.5 Remote Monitoring of Health Status 3.6 Effect of THz Radiation onto Cells and Tissues 3.6.1 Interaction of THz Radiation with DNA Molecules 3.6.2 Interaction of THz Radiation with Living Cells and Tissues 3.6.3 Therapeutic Action of THz Radiation 3.7 Conclusion References Chapter 4 Polarimetric and Spectral Imaging Approach for Meat Quality Control and Characterization of Biological Tissues 4.1 Introduction 4.1.1 Interaction of Light and Tissue 4.1.2 Muscle Structure 4.1.3 Meat Chromophores 4.2 Optical and Imaging Techniques 4.2.1 Optical Spectroscopy Techniques 4.2.1.1 Visible and Near Infrared Spectroscopy 4.2.1.2 Infrared Spectroscopy 4.2.1.3 Fluorescence Spectroscopy 4.2.1.4 Raman Spectroscopy 4.2.1.5 Electrical Impedance Spectroscopy 4.2.2 Emerging Imaging Techniques 4.2.2.1 Hyperspectral Imaging 4.2.2.2 Opto-Magnetic Imaging Spectroscopy 4.2.2.3 Raman Imaging 4.2.2.4 Fluorescence Imaging 4.2.2.5 Thermal Imaging 4.2.2.6 Ultrasound Imaging 4.2.2.7 Tomographic Imaging 4.2.2.8 Polarimetric Imaging 4.3 Experiment and Data Analysis 4.3.1 Visible and Near Infrared Spectroscopy 4.3.1.1 Monte Carlo Simulation 4.3.1.2 Principal Component Analysis 4.3.2 Mueller Matrix Imaging Polarimetry 4.3.2.1 Analysis of MM Elements 4.3.2.2 Statistical Analysis 4.3.3 Two-Point Stokes Vector Diagnostic Approach 4.3.3.1 Theoretical Background 4.3.3.2 Biological Samples 4.3.3.3 Statistical Analysis 4.4 Results and Discussion 4.4.1 Spectroscopic Measurements 4.4.1.1 Analysis of Spectra 4.4.1.2 Monte Carlo Simulations 4.4.1.3 Principal Component Analysis (PCA) 4.4.2 Mueller Matrix Polarimetry Measurements 4.4.2.1 MM Images and FDH Analysis 4.4.2.2 Statistical Analysis 4.4.2.3 Total Depolarization and Scalar Retardance Analysis 4.4.3 Two-point Stokes Vector Diagnosis Approach 4.4.3.1 Tissue with Ordered (Rectilinear) Birefringent Fibrillar Networks – Myocardium Atrium 4.4.3.2 Tissue with Disordered Birefringent Fibrillar Networks—Myocardium Ventricle 4.4.3.3 Intergroup Statistical Analysis of the Modulus Distributions of SCP-Maps 4.5 Summary and Conclusions References Index