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

    Biomedical Signal and Image Examination with Entropy-Based Techniques

    AvB. Thayumanavan,C. Emmanuel

    E-bok
    PDF, Engelska, 2020

    970 kr

    Läs direkt i Bokus Reader – eller ladda ned till din enhet (PDF kräver ofta zoom och scroll på små skärmar).

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    E-bok

    967 kr

    Beskrivning

    The aim of this book is to outline the concept of entropy, various types of entropies and their implementation to evaluate a variety of biomedical signals/images. The book emphasizes various entropy-based image pre-processing methods which are essential for the development of suitable computerized examination systems. The recent research works on biomedical signal evaluation confirms that signal analysis provides vital information regarding the physiological condition of the patient, and the efficient evaluation of these signals can help to diagnose the nature and the severity of the disease. This book emphasizes various entropy-based image pre-processing methods which are essential for the development of suitable computerized examination systems for the analysis of biomedical images recorded with a variety of modalities. The work discusses the image pro-processing methods with the Entropies, such as Kapur, Tsallis, Shannon and Fuzzy on a class of RGB-scaled and gray-scaled medical pictures. The performance of the proposed technique is justified with the help of suitable case studies, which involves x-ray image analysis, MRI analysis and CT analysis. This book is intended for medical signal/image analysts, undergraduate and postgraduate students, researchers, and medical scientists interested in biomedical data evaluation.

    Produktinformation

    • Utgivningsdatum:2020-12-21
    • Språk:Engelska
    • Filformat:PDF
    • Kopieringsskydd:LCP
    • ISBN:9781000327250
    • Förlag:CRC Press

    Utforska kategorier

    • Medicinsk bildbehandling inom Medicin
    • Artificiell intelligens inom Data och IT
    • Systemvetenskap och AI inom Data och IT
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