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Biomedical Imaging
"Biomedical Imaging: Principles and Advancements" offers a captivating exploration of the intricate landscapes within the human body, revealing the transformative power of biomedical imaging. Edited by Wellington Pinheiro dos Santos, Juliana Carneiro Gomes, Maíra Araújo de Santana, and Clarisse Lins de Lima, this anthology delves into foundational concepts, from acquisition to ethical considerations, paving the way for in-depth examinations of magnetic resonance imaging, infrared thermography, and electrical impedance tomography. The real-world applications covered in Section II, from Alzheimer's diagnosis to Covid-19 assessment, showcase the diverse impact of these imaging techniques on healthcare. A collective effort, this volume inspires continued exploration in the ever-evolving field of biomedical imaging.
Biomedical Signal Processing
This book presents the theoretical basis and applications of biomedical signal analysis and processing. Initially, the nature of the most common biomedical signals, such as electroencephalography, electromyography, electrocardiography and others, is described. The theoretical basis of linear signal processing is summarized, with continuous and discrete representation, linear filters and convolutions, Fourier and Wavelets transforms. Machine learning concepts are also presented, from classic methods to deep neural networks. Finally, several applications in neuroscience are presented and discussed, involving diagnosis and therapy, in addition to other applications. Features: Explains signal pr...
Advanced Electroencephalography Analytical Methods
Advanced Electroencephalography Analytical Methods: Fundamentals, Acquisition, and Applications presents the theoretical basis and applications of electroencephalography (EEG) signals in neuroscience, involving signal analysis, processing, signal acquisition, representation, and applications of EEG signal analysis using non-linear approaches and machine learning. It explains principles of neurophysiology, linear signal processing, computational intelligence, and the nature of signals including machine learning. Applications involve computer-aided diagnosis, brain-computer interfaces, rehabilitation engineering, and applied neuroscience. This book: Includes a comprehensive review on biomedica...
Swarm Intelligence
This book presents the fundamentals of swarm intelligence, from classic algorithms to emerging techniques. It presents comprehensive theoretical foundations and examples using the main Computational Intelligence methods in programming languages such as Python, Java and MATLAB®. Real-world applications are also presented in areas as diverse as Medicine, Biology and industrial applications. The book is organized into two parts. The first part provides an introduction to swarming algorithms and hybrid techniques. In the second part, real world applications of swarm intelligence are presented to illustrate how swarm algorithms can be used in applications of optimization and pattern recognition, reviewing the principal methods and methodologies in swarm intelligence.
Intelligent Diagnosis of Lung Cancer and Respiratory Diseases
Intelligent Diagnosis of Lung Cancer and Respiratory Diseases presents information about diseases of the respiratory system and the relevant diagnostic imaging techniques. The book focuses on intelligent diagnostic imaging systems. The first section of the book deals with the physiological underpinnings of 3 major diseases that affect the respiratory system: tuberculosis, lung cancer and COVID-19. This section also explains the basic principles of artificial Intelligence that support the diagnosis of these diseases. The next section presents applications of intelligent systems to support the imaging diagnosis of COVID-19 and lung cancer, with emphasis on digital health and telemedicine approaches. Each chapter is organized into a readable format, and is accompanied with detailed bibliographical information for further reading. This book is a reference for everyone seeking to understand how artificial intelligence can provide solutions for diagnostic support systems by processing and analyzing radiological images to improve early diagnosis and, consequently, lung disease prognosis.
Biomedical Computing for Breast Cancer Detection and Diagnosis
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 B...
Digital Innovation and Global Public Health: Pathways for Sustainable Entry of Digital Innovations into LMIC Health Systems
Digital technologies have rapidly changed how we bank, borrow and lend, commute, or order food. The scale of these changes, and the relatively low barriers for individuals to drive such systemic change, have raised great expectations for digital technologies to also impact health and healthcare globally. The COVID-19 pandemic has further exacerbated the need for improved health data from low- and middle-income countries (LMICs), and the expectation for digital technologies to provide solutions.
Biomedical Signal Processing
This book reports on the latest advances in the study of biomedical signal processing, and discusses in detail a number of open problems concerning clinical, biomedical and neural signals. It methodically collects and presents in a unified form the research findings previously scattered throughout various scientific journals and conference proceedings. In addition, the chapters are self-contained and can be read independently. Accordingly, the book will be of interest to university researchers, R&D engineers and graduate students who wish to learn the core principles of biomedical signal analysis, algorithms, and applications, while also offering a valuable reference work for biomedical engineers and clinicians who wish to learn more about the theory and recent applications of neural engineering and biomedical signal processing.
Evolutionary Computation
This book presents several recent advances on Evolutionary Computation, specially evolution-based optimization methods and hybrid algorithms for several applications, from optimization and learning to pattern recognition and bioinformatics. This book also presents new algorithms based on several analogies and metafores, where one of them is based on philosophy, specifically on the philosophy of praxis and dialectics. In this book it is also presented interesting applications on bioinformatics, specially the use of particle swarms to discover gene expression patterns in DNA microarrays. Therefore, this book features representative work on the field of evolutionary computation and applied sciences. The intended audience is graduate, undergraduate, researchers, and anyone who wishes to become familiar with the latest research work on this field.
