Overview

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.

Full Product Details

9798369398173

Table of Contents

Reviews

Author Information

Muhammad Aamir is an Associate Professor in the Department of Computer Science at Huanggang Normal University, China. He has several years of research experience and has been widely published. M. Aamir has served as a reviewer for many prestigious journals and also served as an organizing member of many international conferences. His research spans multiple areas, including pattern recognition, computer vision, image processing, deep learning, fractional calculus, and organization behavior. 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.

Tab Content 6

Countries Available