This text begins by describing the basic principles and diagnostic applications of optical techniques based on detecting and processing the scattering, fluorescence, FT IR, and Raman spectroscopic signals from various tissues, with an emphasis on blood, epithelial tissues, and human skin. The second half of the volume discusses specific imaging technologies, such as Doppler, laser speckle, optical coherence tomography (OCT), and fluorescence and photoacoustic imaging.
Biomedical optics holds tremendous promise to deliver effective, safe, non- or minimally invasive diagnostics and targeted, customizable therapeutics. Handbook of Biomedical Optics provides an in-depth treatment of the field, including coverage of applications for biomedical research, diagnosis, and therapy. It introduces the theory and fundamental
The Handbook of Photonics for Biomedical Science analyzes achievements, new trends, and perspectives of photonics in its application to biomedicine. With contributions from world-renowned experts in the field, the handbook describes advanced biophotonics methods and techniques intensively developed in recent years.Addressing the latest problems in
Biomedical photonics is currently one of the fastest growing fields, connecting research in physics, optics, and electrical engineering coupled with medical and biological applications. It allows for the structural and functional analysis of tissues and cells with resolution and contrast unattainable by any other methods. However, the major challenges of many biophotonics techniques are associated with the need to enhance imaging resolution even further to the sub-cellular level as well as translate them for in vivo studies. The tissue optical clearing method uses immersion of tissues into optical clearing agents (OCAs) that reduces the scattering of tissue and makes tissue more transparent and this method has been successfully used ever since. This book is a self-contained introduction to tissue optical clearing, including the basic principles and in vitro biological applications, from in vitro to in vivo tissue optical clearing methods, and combination of tissue optical clearing and various optical imaging for diagnosis. The chapters cover a wide range of issues related to the field of tissue optical clearing: mechanisms of tissue optical clearing in vitro and in vivo; traditional and innovative optical clearing agents; recent achievements in optical clearing of different tissues (including pathological tissues) and blood for optical imaging diagnosis and therapy. This book provides a comprehensive account of the latest research and possibilities of utilising optical clearing as an instrument for improving the diagnostic effectiveness of modern optical diagnostic methods. The book is addressed to biophysicist researchers, graduate students and postdocs of biomedical specialties, as well as biomedical engineers and physicians interested in the development and application of optical methods in medicine. Key features: The first collective reference to collate all known knowledge on this topic Edited by experts in the field with chapter contributions from subject area specialists Brings together the two main approaches in immersion optical clearing into one cohesive book
Biomedical optical imaging is a rapidly emerging research area with widespread fundamental research and clinical applications. This book gives an overview of biomedical optical imaging with contributions from leading international research groups who have pioneered many of these techniques and applications. A unique research field spanning the microscopic to the macroscopic, biomedical optical imaging allows both structural and functional imaging. Techniques such as confocal and multiphoton microscopy provide cellular level resolution imaging in biological systems. The integration of this technology with exogenous chromophores can selectively enhance contrast for molecular targets as well as supply functional information on processes such as nerve transduction. Novel techniques integrate microscopy with state-of-the-art optics technology, and these include spectral imaging, two photon fluorescence correlation, nonlinear nanoscopy; optical coherence tomography techniques allow functional, dynamic, nanoscale, and cross-sectional visualization. Moving to the macroscopic scale, spectroscopic assessment and imaging methods such as fluorescence and light scattering can provide diagnostics of tissue pathology including neoplastic changes. Techniques using light diffusion and photon migration are a means to explore processes which occur deep inside biological tissues and organs. The integration of these techniques with exogenous probes enables molecular specific sensitivity.
Shaped by Quantum Theory, Technology, and the Genomics RevolutionThe integration of photonics, electronics, biomaterials, and nanotechnology holds great promise for the future of medicine. This topic has recently experienced an explosive growth due to the noninvasive or minimally invasive nature and the cost-effectiveness of photonic modalities in
This second edition covers the intensive growth in tissue optics--in particular, the field of tissue diagnostics and imaging--that has occurred since 2000. As in the original edition, Part I describes fundamentals and basic research, and Part II presents instrumentation and medical applications. The extensive new material includes results on tissue optical property measurements, including polarized light interaction with turbid tissues; an overview of new polarization imaging and spectroscopy techniques, optical computed tomography (OCT) developments and applications; updates on controlling tissue optical properties, and the optothermal and optoacoustic interaction of light with tissues; and descriptions of fluorescence, nonlinear spectroscopies, and inelastic light scattering.
Lasers have a wide and growing range of applications in medicine. Lasers for Medical Applications summarises the wealth of recent research on the principles, technologies and application of lasers in diagnostics, therapy and surgery.Part one gives an overview of the use of lasers in medicine, key principles of lasers and radiation interactions with tissue. To understand the wide diversity and therefore the large possible choice of these devices for a specific diagnosis or treatment, the respective types of the laser (solid state, gas, dye, and semiconductor) are reviewed in part two. Part three describes diagnostic laser methods, for example optical coherence tomography, spectroscopy, optical biopsy, and time-resolved fluorescence polarization spectroscopy. Those methods help doctors to refine the scope of involvement of the particular body part or, for example, to specify the extent of a tumor. Part four concentrates on the therapeutic applications of laser radiation in particular branches of medicine, including ophthalmology, dermatology, cardiology, urology, gynecology, otorhinolaryngology (ORL), neurology, dentistry, orthopaedic surgery and cancer therapy, as well as laser coatings of implants. The final chapter includes the safety precautions with which the staff working with laser instruments must be familiar.With its distinguished editor and international team of contributors, this important book summarizes international achievements in the field of laser applications in medicine in the past 50 years. It provides a valuable contribution to laser medicine by outstanding experts in medicine and engineering. - Describes the interaction of laser light with tissue - Reviews every type of laser used in medicine: solid state, gas, dye and semiconductor - Describes the use of lasers for diagnostics
A must-have compendium on biomedical telemetry for all biomedical professional engineers, researchers, and graduate students in the field Handbook of Biomedical Telemetry describes the main components of a typical biomedical telemetry system, as well as its technical challenges. Written by a diverse group of experts in the field, it is filled with overviews, highly-detailed scientific analyses, and example applications of biomedical telemetry. The book also addresses technologies for biomedical sensing and design of biomedical telemetry devices with special emphasis on powering/integration issues and materials for biomedical telemetry applications. Handbook of Biomedical Telemetry: Describes the main components of a typical biomedical telemetry system, along with the technical challenges Discusses issues of spectrum regulations, standards, and interoperability—while major technical challenges related to advanced materials, miniaturization, and biocompatibility issues are also included Covers body area electromagnetics, inductive coupling, antennas for biomedical telemetry, intra-body communications, non-RF communication links for biomedical telemetry (optical biotelemetry), as well as safety issues, human phantoms, and exposure assessment to high-frequency biotelemetry fields Presents biosensor network topologies and standards; context-aware sensing and multi-sensor fusion; security and privacy issues in biomedical telemetry; and the connection between biomedical telemetry and telemedicine Introduces clinical applications of Body Sensor Networks (BSNs) in addition to selected examples of wearable, implantable, ingestible devices, stimulator and integrated mobile healthcare system paradigms for monitoring and therapeutic intervention Covering biomedical telemetry devices, biosensor network topologies and standards, clinical applications, wearable and implantable devices, and the effects on the mobile healthcare system, this compendium is a must-have for professional engineers, researchers, and graduate students.
Deep Learning (DL) is a method of machine learning, running over Artificial Neural Networks, that uses multiple layers to extract high-level features from large amounts of raw data. Deep Learning methods apply levels of learning to transform input data into more abstract and composite information. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications gives readers a complete overview of the essential concepts of Deep Learning and its applications in the field of Biomedical Engineering. Deep learning has been rapidly developed in recent years, in terms of both methodological constructs and practical applications. Deep Learning provides computational models of multiple processing layers to learn and represent data with higher levels of abstraction. It is able to implicitly capture intricate structures of large-scale data and is ideally suited to many of the hardware architectures that are currently available. The ever-expanding amount of data that can be gathered through biomedical and clinical information sensing devices necessitates the development of machine learning and AI techniques such as Deep Learning and Convolutional Neural Networks to process and evaluate the data. Some examples of biomedical and clinical sensing devices that use Deep Learning include: Computed Tomography (CT), Magnetic Resonance Imaging (MRI), Ultrasound, Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), Magnetic Particle Imaging, EE/MEG, Optical Microscopy and Tomography, Photoacoustic Tomography, Electron Tomography, and Atomic Force Microscopy. Handbook for Deep Learning in Biomedical Engineering: Techniques and Applications provides the most complete coverage of Deep Learning applications in biomedical engineering available, including detailed real-world applications in areas such as computational neuroscience, neuroimaging, data fusion, medical image processing, neurological disorder diagnosis for diseases such as Alzheimer's, ADHD, and ASD, tumor prediction, as well as translational multimodal imaging analysis. - Presents a comprehensive handbook of the biomedical engineering applications of DL, including computational neuroscience, neuroimaging, time series data such as MRI, functional MRI, CT, EEG, MEG, and data fusion of biomedical imaging data from disparate sources, such as X-Ray/CT - Helps readers understand key concepts in DL applications for biomedical engineering and health care, including manifold learning, classification, clustering, and regression in neuroimaging data analysis - Provides readers with key DL development techniques such as creation of algorithms and application of DL through artificial neural networks and convolutional neural networks - Includes coverage of key application areas of DL such as early diagnosis of specific diseases such as Alzheimer's, ADHD, and ASD, and tumor prediction through MRI and translational multimodality imaging and biomedical applications such as detection, diagnostic analysis, quantitative measurements, and image guidance of ultrasonography
