COVID-19 Radiological Lung Imaging: A Classic Artificial Intelligence Framework

· ·
· Academic Press
Ebook
450
Pages
Eligible
This book will become available on November 8, 2025. You will not be charged until it is released.

About this ebook

COVID-19 Radiological Lung Imaging: A Classic Artificial Intelligence Framework introduces modern AI technologies for early detection of COVID-19 disease to assist in saving patient lives and safeguarding frontline workers. With a strong focus on Deep Learning, the book examines specific detection and classification techniques in lung X-ray imaging, computed tomography lung imaging, deep learning on edge devises and bias measurements, deep learning for cloud and explainable AI for validation, and discusses the medical impact and AI implications for COVID-19 in lung pathologies. It is therefore an ideal reference for researchers and clinicians working in radiology and pulmonary medicine to learn the modern AI technologies in COVID-19 paradigms for implementation. - Offers broad and complete coverage in AI in healthcare regarding detection, classification, explainable AI, cloud-based diagnosis, pruning, and bias technologies in radiology - Reviews AI systems technology that can be incorporated into medical devices as well as in many diagnoses and treatment procedures - Contributes to early detection techniques of COVID-19 disease through AI technologies

About the author

Luca Saba is Dean of School of Medicine at the University of Cagliari, full professor of Radiology and Chief of the Department of Radiology in the A.O.U. of Cagliari. Professor Saba’s research is focused on Multi-Detector-Row Computed Tomography, Magnetic Resonance, Ultrasound, Neuroradiology, and Diagnostic in Vascular Sciences. His works have achieved more than 700 high impact factor in notable peer-reviewed journals such as The New England Journal of Medicine, Lancet Neurology, Circulation Radiology, American Journal of Neuroradiology, Atherosclerosis, European Radiology. He has spoken over 150 times at national and international levels and won 22 scientific and extracurricular awards during his career. Dr Saba has presented more than 500 papers and posters in National and International Congress (RSNA, ESGAR, ECR, ISR, AOCR, AINR, JRS, SIRM, AINR). He has written 43 book-chapters and is Editor of 19 books in the field of Computed Tomography, Cardiovascular, Plastic Surgery, Gynecological Imaging and Neurodegenerative imaging.

Sushant Agarwal, BE, is currently a software engineer with Tech-Net Inc and has experience with working on edge devices such as Raspberry Pie, NVIDIA Jetson Nano, and Intel Neural compute stick. He is passionate about deep learning and has a good command of Python, SQL, Deep Learning, and Computer Vision. Sushant Agarwal holds Udacity Nanodegrees in Deep Learning and Data Science as well as a Specialization in Artificial Intelligence for Medical Imaging and has been a top performer in various national and international competitions. He has published over 11 research papers internationally in the field of computer vision and deep learning.

Dr. Jasjit Suri, PhD, MBA, is a renowned innovator and scientist. He received the Director General’s Gold Medal in 1980 and is a Fellow of several prestigious organizations, including the American Institute of Medical and Biological Engineering and the Institute of Electrical and Electronics Engineers. Dr. Suri has been honored with lifetime achievement awards from Marcus, NJ, USA, and Graphics Era University, India. He has published nearly 300 peer-reviewed AI articles, 100 books, and holds 100 innovations/trademarks, achieving an H-index of nearly 100 with about 43,000 citations. Dr. Suri has served as chairman of AtheroPoint, IEEE Denver section, and as an advisory board member to various healthcare industries and universities globally.

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