Deep Learning in Medical Signal and Image Processing

Muhammad Aamir, Uzair Aslam Bhatti, Ziaur Rahman , Jameel Ahmed Bhutto

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English

Medical Information Science Reference
23 May 2025

Medical imaging; Communications engineering & telecommunications; Artificial intelligence; Signal processing

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.

Edited by: Muhammad Aamir, Uzair Aslam Bhatti, Ziaur Rahman, Jameel Ahmed Bhutto, Waheed Ahmed Abro
Imprint: Medical Information Science Reference
Country of Publication: United States
Dimensions: Height: 279mm, Width: 216mm,
ISBN: 9798369398173
Pages: 630
Publication Date: 23 May 2025
Audience: College/higher education , Professional and scholarly , Primary , Undergraduate
Format: Paperback
Publisher's Status: Active

Muhammad Aamir received his Bachelor of Engineering degree in Computer Systems Engineering from Mehran University of Engineering & Technology, Jamshoro, Sindh, Pakistan, in 2008. He went on to earn a Master of Engineering degree in Software Engineering from Chongqing University, China, in 2014, and later completed his PhD in Computer Science and Technology from Sichuan University, Chengdu, China, in 2019. Currently, he is an Associate Professor in the College of Computer Science at Huanggang Normal University, China. With extensive research experience and a prolific publication record, Dr. Aamir has made significant contributions to various fields including pattern recognition, computer vision, medical image processing, deep learning, and fractional calculus. His expertise and dedication to advancing these areas have earned him recognition as a peer reviewer for numerous prestigious journals and as an organizing committee member for several international conferences. Uzair Aslam Bhatti was born in 1986. He received the Ph.D. degree in information and communication engineering, Hainan University, Haikou, Hainan, in 2019. He is pursuing the Postdoctoral degree in implementing Clifford algebra algorithms in analyzing the geospatial data using artificial intelligence (AI) with Nanjing Normal University, Nanjing, China. His areas of specialty include AI, machine learning, and image processing. Ziaur Rahman has joined the Department of Computer Science, Huanggang Normal University, Hubei, China as a Distinguish Associate Professor in November 2021. Currently, he is an associate professor in Huanggang Normal University. Before that, he received Ph.D degree in Computer Science from Sichuan University, Chengdu, China in 2021 and a Master degree in Software Engineering from Chongqing University, Chongqing, China in 2017. His research interests cover image processing, computer vision, and deep learning, with a special emphasis on low-light image enhancement. Specifically, he is dedicated to designing learning frameworks by exploring the physical properties of various vision applications, including low-light image enhancement, dehazing, denoising, and underwater image enhancement. He is also interested in exploring learning algorithms for medical image analysis. Jameel Ahmed Bhutto received his Bachelor of Engineering in Telecommunication Engineering from Mehran University of Engineering and Technology, Pakistan in 2010. He received his Master of Engineering degree in Communication Systems and Networking from Mehran University of Engineering and Technology, Pakistan in 2016. He has completed his PhD degree from South China University of Technology, China in 2022. He is working as a distinguished associate professor at the Department of Computer Science, Huanggang Normal University, China. His major research interests include pattern recognition, deep learning, computer vision, image fusion, image enhancement and digital image processing.