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Published by Cambridge University Press, 2023
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Published by Cambridge University Press, 2023
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Published by Cambridge University Press, 2023
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Published by Cambridge University Press, Cambridge, 2023
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Hardcover. Condition: new. Hardcover. Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. The background theory of deep learning is introduced step-by-step, and by incorporating modeling fundamentals this book explains how to implement deep learning in a variety of modalities, including X-ray, CT, MRI and others. Real-world examples demonstrate an interdisciplinary approach to medical image reconstruction processes, featuring numerous imaging applications. Recent clinical studies and innovative research activity in generative models and mathematical theory will inspire the reader towards new frontiers. This book is ideal for graduate students in Electrical or Biomedical Engineering or Medical Physics. Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. Including interdisciplinary examples and a step-by-step background of deep learning, this book provides insight into the future of biomedical image reconstruction with clinical studies and mathematical theory. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Published by Cambridge University Press, 2023
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Published by Elsevier Science & Technology, 2023
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Published by Cambridge University Press, Cambridge, 2023
ISBN 10: 1316517519 ISBN 13: 9781316517512
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Hardcover. Condition: new. Hardcover. Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. The background theory of deep learning is introduced step-by-step, and by incorporating modeling fundamentals this book explains how to implement deep learning in a variety of modalities, including X-ray, CT, MRI and others. Real-world examples demonstrate an interdisciplinary approach to medical image reconstruction processes, featuring numerous imaging applications. Recent clinical studies and innovative research activity in generative models and mathematical theory will inspire the reader towards new frontiers. This book is ideal for graduate students in Electrical or Biomedical Engineering or Medical Physics. Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. Including interdisciplinary examples and a step-by-step background of deep learning, this book provides insight into the future of biomedical image reconstruction with clinical studies and mathematical theory. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Published by Cambridge University Press, 2023
ISBN 10: 1316517519 ISBN 13: 9781316517512
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Hardcover. Condition: Brand New. 400 pages. 9.84x6.85x0.94 inches. In Stock.
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Published by Cambridge University Press Dez 2023, 2023
ISBN 10: 1316517519 ISBN 13: 9781316517512
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Buch. Condition: Neu. Neuware - Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. Including interdisciplinary examples and a step by step background of deep learning, this book provides insight into the future of biomedical image reconstruction with clinical studies and mathematical theory.
Language: English
Published by Cambridge University Press, Cambridge, 2023
ISBN 10: 1316517519 ISBN 13: 9781316517512
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Hardcover. Condition: new. Hardcover. Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. The background theory of deep learning is introduced step-by-step, and by incorporating modeling fundamentals this book explains how to implement deep learning in a variety of modalities, including X-ray, CT, MRI and others. Real-world examples demonstrate an interdisciplinary approach to medical image reconstruction processes, featuring numerous imaging applications. Recent clinical studies and innovative research activity in generative models and mathematical theory will inspire the reader towards new frontiers. This book is ideal for graduate students in Electrical or Biomedical Engineering or Medical Physics. Discover the power of deep neural networks for image reconstruction with this state-of-the-art review of modern theories and applications. Including interdisciplinary examples and a step-by-step background of deep learning, this book provides insight into the future of biomedical image reconstruction with clinical studies and mathematical theory. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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Condition: New. Inhaltsverzeichnis1. Introduction to Deep Learning and Diagnosis in Medicine2. 1D CNN based identification of Sleep disorders using EEG signals3. Classification of Histopathological Colon Cancer Images Using PSO based Feature Sel.
Language: English
Published by Elsevier Science & Technology Mai 2023, 2023
ISBN 10: 0323961290 ISBN 13: 9780323961295
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Neuware - 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.
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Paperback. Condition: Brand New. 300 pages. 9.25x7.50x0.63 inches. In Stock. This item is printed on demand.