Magnetic Resonance Imaging
Recording, Reconstruction and Assessment
Published on 17. February 2022
Book
Paperback/Softback
188 pages
978-0-12-823401-3 (ISBN)
Description
Magnetic Resonance Imaging: Recording, Reconstruction and Assessment gives a detailed overview of magnetic resonance imaging (MRI), along with its applications and challenges. The book explores the abnormalities in internal human organs using MRI techniques while also featuring case studies that illustrate measures used. In addition, it explores precautionary measures used during MRI based imaging, the selection of appropriate contrast agents, and the selection of the appropriate modality during the image registration. Sections introduce medical imaging, the use of MRI in brain, cardiac, lung and kidney detection, and also discuss both 2D and 3D imaging techniques and various MRI modalities.
This volume will be of interest to researchers, engineers and medical professionals involved in the development and use of MRI systems.
This volume will be of interest to researchers, engineers and medical professionals involved in the development and use of MRI systems.
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
Professional and scholarly
This book series is useful to professional researchers in medical image processing, biomedical engineering, and physicians. This book series will attract numerous researchers working in the healthcare systems. The book is primarily intended for researchers from academia and industry, who are working in the research areas of: Biomedical engineering computer- aided detection and diagnosis, medical devices requirements, tele-medicine, and systems monitoring, Wearable Sensors Devices, Monitoring Systems Design, Healthcare Real Applications.Electrical and Electronics Engineering: sensors design, body area networking, monitoring systems design, commercial wearable devices, and design of medical imaging modalities.Communications Engineering: wireless communication systems, monitoring systems, and secure communication facilities. Computer Engineering: algorithms and simulation issues related to medical imaging system and CAD systems.
Product notice
Paperback (trade)
Illustrations
Approx. 200 illustrations (200 in full color); Illustrations
Dimensions
Height: 235 mm
Width: 191 mm
Thickness: 10 mm
Weight
338 gr
ISBN-13
978-0-12-823401-3 (9780128234013)
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
E-Book
02/2022
Academic Press
€86.95
Available for download
Persons
Professor V. Rajinikanth works in the Department of Electronics and Instrumentation Engineering at St. Joseph's College of Engineering in Chennai, Tamilnadu, India. Nilanjan Dey (Senior Member, IEEE) received the B.Tech., M.Tech. in information technology from West Bengal Board of Technical University and Ph.D. degrees in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, in 2005, 2011, and 2015, respectively. Currently, he is Associate Professor with the Techno International New Town, Kolkata and a visiting fellow of the University of Reading, UK. He has authored over 300 research articles in peer-reviewed journals and international conferences and 40 authored books. His research interests include medical imaging and machine learning. Moreover, he actively participates in program and organizing committees for prestigious international conferences, including World Conference on Smart Trends in Systems Security and Sustainability (WorldS4), International Congress on Information and Communication Technology (ICICT), International Conference on Information and Communications Technology for Sustainable Development (ICT4SD) etc.
He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.
He is also the Editor-in-Chief of International Journal of Ambient Computing and Intelligence, Associate Editor of IEEE Transactions on Technology and Society and series Co-Editor of Springer Tracts in Nature-Inspired Computing and Data-Intensive Research from Springer Nature and Advances in Ubiquitous Sensing Applications for Healthcare from Elsevier etc. Furthermore, he was an Editorial Board Member Complex & Intelligence Systems, Springer, Applied Soft Computing, Elsevier and he is an International Journal of Information Technology, Springer, International Journal of Information and Decision Sciences etc. He is a Fellow of IETE and member of IE, ISOC etc.
Content
1. Introduction to Image Assisted Disease Screening
2. Magnetic Resonance Imaging - Recording and Reconstruction
3. Image Processing Schemes to Enhance Disease Information in MRI Slices
4. Segmentation of Tumor in Breast MRI Using Entropy Thresholding and Mayfly-Algorithm: A Study
5. Abnormality Detection in Heart MRI with Spotted-Hyena-Algorithm Supported Kapur/Otsu Thresholding and Level-Set Segmentation
6. CNN based Segmentation of Brain Tumor from T2-Weighted MRI Slices
7. Automated Detection of Ischemic-Stroke with Brain MRI using Machine-Learning and Deep-Learning Features
2. Magnetic Resonance Imaging - Recording and Reconstruction
3. Image Processing Schemes to Enhance Disease Information in MRI Slices
4. Segmentation of Tumor in Breast MRI Using Entropy Thresholding and Mayfly-Algorithm: A Study
5. Abnormality Detection in Heart MRI with Spotted-Hyena-Algorithm Supported Kapur/Otsu Thresholding and Level-Set Segmentation
6. CNN based Segmentation of Brain Tumor from T2-Weighted MRI Slices
7. Automated Detection of Ischemic-Stroke with Brain MRI using Machine-Learning and Deep-Learning Features