Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods
Language: English
Published by Elsevier Inc Jun 2023, 2023
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Condition: New
US$ 394.65
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Add to basketItem description from seller
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.…
Seller Inventory # 9780323961295
- Title
- Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods
- Author
- Saban Öztürk
- Publisher
- Elsevier Inc Jun 2023
- Publication year
- 2023
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0323961290
- ISBN 13
- 9780323961295
- Item weight
- 524 grams
- Dimensions
- 235x191x16 mm
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
"Synopsis" may belong to another edition of this title.
About the Author
Dr. Şaban Öztürk is a researcher in Amasya University, in Turkey. He has over 50 scientific publications. Dr. Öztürk’s current research interests are in the fields of biomedical image processing, histopathological image analysis, hashing, content-based image retrieval, siamese networks and loss function, metric learning, deep learning, and image representation.
"About the title" may belong to another edition of this title.
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