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Autor(en): 
  • Grigoryan Artyom M.
  • Grigoryan Merughan M.
  • Image Processing: Tensor Transform and Discrete Tomography with MATLAB ® 
     

    (Buch)
    Dieser Artikel gilt, aufgrund seiner Grösse, beim Versand als 3 Artikel!


    Übersicht

    Auf mobile öffnen
     
    Lieferstatus:   Auf Bestellung (Lieferzeit unbekannt)
    Veröffentlichung:  Oktober 2012  
    Genre:  Naturwissensch., Medizin, Technik 
     
    advanced CT image processing techniques / Cartesian Grid / Cartesian Lattice / computed tomography algorithms / COMPUTERS / Optical Data Processing / Convolution Equation / Diagonal Projection / Direction Images
    ISBN:  9781466509948 
    EAN-Code: 
    9781466509948 
    Verlag:  Taylor and Francis 
    Einband:  Gebunden  
    Sprache:  English  
    Dimensionen:  H 229 mm / B 152 mm / D  
    Gewicht:  771 gr 
    Seiten:  468 
    Illustration:  schwarz-weiss Illustrationen, Tabellen, schwarz-weiss 
    Bewertung: Titel bewerten / Meinung schreiben
    Inhalt:
    Focusing on mathematical methods in computer tomography, Image Processing: Tensor Transform and Discrete Tomography with MATLAB® introduces novel approaches to help in solving the problem of image reconstruction on the Cartesian lattice. Specifically, it discusses methods of image processing along parallel rays to more quickly and accurately reconstruct images from a finite number of projections, thereby avoiding overradiation of the body during a computed tomography (CT) scan. The book presents several new ideas, concepts, and methods, many of which have not been published elsewhere. New concepts include methods of transferring the geometry of rays from the plane to the Cartesian lattice, the point map of projections, the particle and its field function, and the statistical model of averaging. The authors supply numerous examples, MATLAB®-based programs, end-of-chapter problems, and experimental results of implementation. The main approach for image reconstruction proposed by the authors differs from existing methods of back-projection, iterative reconstruction, and Fourier and Radon filtering. In this book, the authors explain how to process each projection by a system of linear equations, or linear convolutions, to calculate the corresponding part of the 2-D tensor or paired transform of the discrete image. They then describe how to calculate the inverse transform to obtain the reconstruction. The proposed models for image reconstruction from projections are simple and result in more accurate reconstructions. Introducing a new theory and methods of image reconstruction, this book provides a solid grounding for those interested in further research and in obtaining new results. It encourages readers to develop effective applications of these methods in CT.

      



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