Artificial Intelligence-based Infrared Thermal Image Processing and its Applications

Artificial Intelligence-based Infrared Thermal Image Processing and its Applications

Author: U. Snekhalatha

Publisher: CRC Press

Published: 2022-09-28

Total Pages: 272

ISBN-13: 1000688453

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Infrared thermography is a fast and non-invasive technology that provides a map of the temperature distribution on the body’s surface. This book provides a description of designing and developing a computer-assisted diagnosis (CAD) system based on thermography for diagnosing such common ailments as rheumatoid arthritis (RA), diabetes complications, and fever. It also introduces applications of machine-learning and deep-learning methods in the development of CAD systems. Key Features: Covers applications of various image processing techniques in thermal imaging applications for the diagnosis of different medical conditions Describes the development of a computer diagnostics system (CAD) based on thermographic data Discusses deep-learning models for accurate diagnosis of various diseases Includes new aspects in rheumatoid arthritis and diabetes research using advanced analytical tools Reviews application of feature fusion algorithms and feature reduction algorithms for accurate classification of images This book is aimed at researchers and graduate students in biomedical engineering, medicine, image processing, and CAD.


Artificial Intelligence-based Infrared Thermal Image Processing and its Applications

Artificial Intelligence-based Infrared Thermal Image Processing and its Applications

Author: U. Snekhalatha

Publisher: CRC Press

Published: 2022-09-28

Total Pages: 247

ISBN-13: 1000688402

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Infrared thermography is a fast and non-invasive technology that provides a map of the temperature distribution on the body’s surface. This book provides a description of designing and developing a computer-assisted diagnosis (CAD) system based on thermography for diagnosing such common ailments as rheumatoid arthritis (RA), diabetes complications, and fever. It also introduces applications of machine-learning and deep-learning methods in the development of CAD systems. Key Features: Covers applications of various image processing techniques in thermal imaging applications for the diagnosis of different medical conditions Describes the development of a computer diagnostics system (CAD) based on thermographic data Discusses deep-learning models for accurate diagnosis of various diseases Includes new aspects in rheumatoid arthritis and diabetes research using advanced analytical tools Reviews application of feature fusion algorithms and feature reduction algorithms for accurate classification of images This book is aimed at researchers and graduate students in biomedical engineering, medicine, image processing, and CAD.


Infrared Thermography

Infrared Thermography

Author: Raghu Prakash

Publisher: BoD – Books on Demand

Published: 2012-03-14

Total Pages: 250

ISBN-13: 9535102427

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Infrared Thermography (IRT) is commonly as a NDE tool to identify damages and provide remedial action. The fields of application are vast, such as, materials science, life sciences and applied engineering. This book offers a collection of ten chapters with three major sections - relating to application of infrared thermography to study problems in materials science, agriculture, veterinary and sports fields as well as in engineering applications. Both mathematical modeling and experimental aspects of IRT are evenly discussed in this book. It is our sincere hope that the book meets the requirements of researchers in the domain and inspires more researchers to study IRT.


Infrared Thermal Imaging

Infrared Thermal Imaging

Author: Michael Vollmer

Publisher: John Wiley & Sons

Published: 2018-02-20

Total Pages: 803

ISBN-13: 3527413510

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This new up-to-date edition of the successful handbook and ready reference retains the proven concept of the first, covering basic and advanced methods and applications in infrared imaging from two leading expert authors in the field. All chapters have been completely revised and expanded and a new chapter has been added to reflect recent developments in the field and report on the progress made within the last decade. In addition there is now an even stronger focus on real-life examples, with 20% more case studies taken from science and industry. For ease of comprehension the text is backed by more than 590 images which include graphic visualizations and more than 300 infrared thermography figures. The latter include many new ones depicting, for example, spectacular views of phenomena in nature, sports, and daily life.


Handbook of Research on Advanced Mechatronic Systems and Intelligent Robotics

Handbook of Research on Advanced Mechatronic Systems and Intelligent Robotics

Author: Habib, Maki K.

Publisher: IGI Global

Published: 2019-07-26

Total Pages: 484

ISBN-13: 1799801381

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Advanced research in the field of mechatronics and robotics represents a unifying interdisciplinary and intelligent engineering science paradigm. It is a holistic, concurrent, and interdisciplinary engineering science that identifies novel possibilities of synergizing and fusing different disciplines. The Handbook of Research on Advanced Mechatronic Systems and Intelligent Robotics is a collection of innovative research on the methods and applications of knowledge in both theoretical and practical skills of intelligent robotics and mechatronics. While highlighting topics including green technology, machine learning, and virtual manufacturing, this book is ideally designed for researchers, students, engineers, and computer practitioners seeking current research on developing innovative ideas for intelligent robotics and autonomous and smart interdisciplinary mechatronic products.


Application of Infrared to Biomedical Sciences

Application of Infrared to Biomedical Sciences

Author: Eddie YK Ng

Publisher: Springer

Published: 2017-03-23

Total Pages: 560

ISBN-13: 9811031479

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The book covers the latest updates in the application of infrared to biomedical sciences, a non-invasive, contactless, safe and easy approach imaging of skin and tissue temperatures. Its diagnostic procedure allows practitioners to identify the locations of abnormal chemical and blood vessel activity such as angiogenesis in body tissue. Its non-invasive approach works by applying the technology of the infrared camera and state-of-the-art software, where high-resolution digital infrared imaging technology benefits highly from enhanced image production, standardized image interpretation protocols, computerized comparison and storage, and sophisticated image enhancement and analysis. The book contains contributions from global prominent scientists in the area of infrared applications in biomedical studies. The target audience includes academics, practitioners, clinicians and students working in the area of infrared imaging in biomedicine.


Fundamentals and Methods of Machine and Deep Learning

Fundamentals and Methods of Machine and Deep Learning

Author: Pradeep Singh

Publisher: John Wiley & Sons

Published: 2022-02-01

Total Pages: 480

ISBN-13: 1119821886

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FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.


Practical Machine Learning and Image Processing

Practical Machine Learning and Image Processing

Author: Himanshu Singh

Publisher: Apress

Published: 2019-02-26

Total Pages: 177

ISBN-13: 1484241495

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Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using real-life scenarios. After reading this book you will be able to apply image processing techniques and make machine learning models for customized application. What You Will LearnDiscover image-processing algorithms and their applications using Python Explore image processing using the OpenCV library Use TensorFlow, scikit-learn, NumPy, and other libraries Work with machine learning and deep learning algorithms for image processing Apply image-processing techniques to five real-time projects Who This Book Is For Data scientists and software developers interested in image processing and computer vision.


Biomedical Computing for Breast Cancer Detection and Diagnosis

Biomedical Computing for Breast Cancer Detection and Diagnosis

Author: Pinheiro dos Santos, Wellington

Publisher: IGI Global

Published: 2020-07-17

Total Pages: 357

ISBN-13: 1799834573

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Despite success with treatment when diagnosed early, breast cancer is still one of the most fatal forms of cancer for women. Imaging diagnosis is still one of the most efficient ways to detect early breast changes with mammography among the most used techniques. However, there are other techniques that have emerged as alternatives or even complementary tests in the early detection of breast lesions (e.g., breast thermography and electrical impedance tomography). Artificial intelligence can be used to optimize image diagnosis, increasing the reliability of the reports and supporting professionals who do not have enough knowledge or experience to make good diagnoses. Biomedical Computing for Breast Cancer Detection and Diagnosis is a collection of research that presents a review of the physiology and anatomy of the breast; the dynamics of breast cancer; principles of pattern recognition, artificial neural networks, and computer graphics; and the breast imaging techniques and computational methods to support and optimize the diagnosis. While highlighting topics including mammograms, thermographic imaging, and intelligent systems, this book is ideally designed for medical oncologists, surgeons, biomedical engineers, medical imaging professionals, cancer researchers, academicians, and students in medicine, biomedicine, biomedical engineering, and computer science.