Computer Methods And Programs In Biomedical Signal And Image Processing
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Computer Methods and Programs in Biomedical Signal and Image Processing
This book aims to provide a brief update to the current status of and advances in computational methods and programs used for the development of the theory and practice of biomedical signal and image communication. The book comprises a collection of invited manuscripts, written in a convenient way and of manageable length. These timely collections will provide an invaluable resource for initial inquiries into technologies and will encapsulate the latest developments and applications with reference sources for further detailed information. The methods described in this book cover a wide range of computational algorithms that are widely used in bioengineering and biomedicine. The content and format are specifically designed to stimulate the further development and application of these technologies by reaching out to non-specialists across a broad audience. This book is intended to expose the latest developments of scientists and engineers covering a variety of complementary topics, to enhance people's overall understanding of computer science and biomedical image communications. It will benefit students, scientists, and researchers in applied computer science. Engineers and clinicians working in imaging will also find this book useful.
Biomedical Signal and Image Processing
Written for senior-level and first year graduate students in biomedical signal and image processing, this book describes fundamental signal and image processing techniques that are used to process biomedical information. The book also discusses application of these techniques in the processing of some of the main biomedical signals and images, such as EEG, ECG, MRI, and CT. New features of this edition include the technical updating of each chapter along with the addition of many more examples, the majority of which are MATLAB based.
Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods
Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research on both medical imaging and medical signals analysis. The book discusses classification, segmentation, detection, tracking and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT and X-RAY, amongst others. These image and signal modalities include real challenges that are the main themes that medical imaging and medical signal processing researchers focus on today. The book also emphasizes removing noise and specifying dataset key properties, with each chapter containing details of one of the medical imaging or medical signal modalities. Focusing on solving real medical problems using new deep learning and CNN approaches, this book will appeal to research scholars, graduate students, faculty members, R&D engineers, and biomedical engineers who want to learn how medical signals and images play an important role in the early diagnosis and treatment of diseases. - Investigates novel concepts of deep learning for acquisition of non-invasive biomedical image and signal modalities for different disorders - Explores the implementation of novel deep learning and CNN methodologies and their impact studies that have been tested on different medical case studies - Presents end-to-end CNN architectures for automatic detection of situations where early diagnosis is important - Includes novel methodologies, datasets, design and simulation examples