
Deep Learning in Medical Signal and Image Processing
IGI Global (Publisher)
Published on 23. May 2025
Book
Hardback
500 pages
979-8-3693-9816-6 (ISBN)
Description
Deep learning is revolutionizing the analysis of medical signals and images, offering unprecedented advancements in diagnostic accuracy and efficiency. Techniques such as convolutional and recurrent neural networks are transforming the processing of radiological scans, ultrasound images, and ECG readings. By enabling more detailed and precise interpretations, deep learning enhances the ability of healthcare providers to make timely and informed decisions. These innovations are reshaping medical workflows, improving patient outcomes, and paving the way for a future of more reliable and efficient healthcare solutions. Deep Learning in Medical Signal and Image Processing offers a comprehensive examination of deep learning, specifically through convolutional neural networks (CNNs) and recurrent neural networks (RNNs), to medical data. It explores the application of AI in the analysis of medical signals and images. Covering topics such as diagnostic accuracy, enhanced decision-making, and data augmentation techniques, this book is an excellent resource for medical practitioners, clinicians, data scientists, AI researchers, healthcare professionals, engineers, professionals, researchers, scholars, academicians, and more.
More details
Language
English
Target group
College/higher education
Professional and scholarly
Product notice
sewn/stitched
Cloth over boards
Dimensions
Height: 286 mm
Width: 221 mm
Thickness: 38 mm
Weight
1826 gr
ISBN-13
979-8-3693-9816-6 (9798369398166)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Muhammad Aamir | Uzair Aslam Bhatti | Ziaur Rahman
Deep Learning in Medical Signal and Image Processing
Book
05/2025
Medical Information Science Reference
€307.10
Shipment within 10-20 days