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    1. Medicin
    2. Andra medicinska specialiteter
    3. Medicinsk bildbehandling

    Magnetic Resonance Imaging

    Recording, Reconstruction and Assessment

    AvV. Rajinikanth,Nilanjan Dey

    Häftad, Engelska, 2022

    Del i serien Primers in Biomedical Imaging Devices and Systems

    995 kr

    Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

    Beskrivning

    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.



    • Discusses challenges and issues faced, as well as safety precautions to be followed
    • Features case studies with benchmark MRIs existing in the literature
    • Introduces computer-based assessment (Machine Learning and Deep Learning) of the MRI based on its 2D slices

    Produktinformation

    • Utgivningsdatum:2022-02-17
    • Mått:191 x 235 x 19 mm
    • Vikt:410 g
    • Format:Häftad
    • Språk:Engelska
    • Serie:Primers in Biomedical Imaging Devices and Systems
    • Antal sidor:188
    • Förlag:Elsevier Science
    • ISBN:9780128234013

    Utforska kategorier

    • Medicinsk bildbehandling inom Medicin

    Mer om författaren

    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.

    Innehållsförteckning

    • 1. Introduction to Image Assisted Disease Screening2. Magnetic Resonance Imaging – Recording and Reconstruction3. Image Processing Schemes to Enhance Disease Information in MRI Slices4. Segmentation of Tumor in Breast MRI Using Entropy Thresholding and Mayfly-Algorithm: A Study5. Abnormality Detection in Heart MRI with Spotted-Hyena-Algorithm Supported Kapur/Otsu Thresholding and Level-Set Segmentation6. CNN based Segmentation of Brain Tumor from T2-Weighted MRI Slices7. Automated Detection of Ischemic-Stroke with Brain MRI using Machine-Learning and Deep-Learning Features
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