Diagnostic Biomedical Signal and Image Processing Applications With Deep Learning Methods (Intelligent Data-Centric Systems) - Softcover

Softcover

ISBN 10: 0323961290 ISBN 13: 9780323961295

Publisher: Academic Press, 2023

Synopsis

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

About this title

About the Authors

Professor Dr. Kemal Polat is a Professor in the Electrical and Electronic Engineering Department, Engineering of Faculty, Bolu Abant Izzet Baysal University, in Turkey. He has over 130 articles published in leading scientific journals and around 80 international conference papers. He is, amongst others, a member of the editorial board of the Journal of Neural Computing and Applications and editorial board member of Applied Soft Computing, Elsevier. His current research interests are in biomedical signal classification, control systems, electronics, statistical signal processing, visual memory, neuroscience, brain-computer interface, PPG signal, medical electronics, digital signal processing, pattern recognition, and classification.

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.

From the Back Cover

Analysis of medical signals and images plays an important role in the early diagnosis and treatment of diseases. Thanks to the development of technology, widespread use of medical imaging devices has become beneficial to human health. However, despite advances in technology, the number of patients and the workload of healthcare professionals is ever increasing. Deep learning methods and approaches have the potential to help relieve the workload of doctors and facilitate early diagnosis. This can help to improve the healthcare system and people's quality of life.

Diagnostic Biomedical Signal and Image Processing Applications with Deep Learning Methods presents comprehensive research focusing on both medical imaging and medical signals analysis. It discusses classification, segmentation, detection, tracking, and retrieval applications of non-invasive methods such as EEG, ECG, EMG, MRI, fMRI, CT, and X-RAY, among others. These image and signal modalities include real challenges, which are the main themes that medical imaging and medical signal processing researchers focus on today. The proposed 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.

Edition details

• Publisher: Academic Press
• Publication date: 2023
• Language: English
• ISBN 10: 0323961290
• ISBN 13: 9780323961295
• Binding: Paperback
• Edition number: 1
• Number of pages: 302
• Editor: Polat, Öztürk