Fundamentals of Computerized Tomography Image Reconstruction from Projections 2nd Edition by Gabor T Herman ISBN 1846287235 9781846287237

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ISBN 10: 1846287235
ISBN 13: 9781846287237
Author: Gabor T. Herman

This revised and updated text presents the computational and mathematical procedures underlying data collection, image reconstruction, and image display in computerized tomography. New topics: the fast calculation of a ray sum for a digitized picture, the task-oriented comparison of reconstruction algorithm performance, blob basis functions and the linogram method for image reconstruction. Features: Describes how projection data are obtained and the resulting reconstructions are used; Presents a comparative evaluation of reconstruction methods; Investigates reconstruction algorithms; Explores basis functions, functions to be optimized, norms, generalized inverses, least squares solutions, maximum entropy solutions, and most likely estimates; Discusses SNARK09, a large programming system for image reconstruction; Concludes each chapter with helpful Notes and References sections. An excellent guide for practitioners, it can also serve as a textbook for an introductory graduate course.

Fundamentals of Computerized Tomography Image Reconstruction from Projections 2nd Table of contents:

• Mathematical Foundations for Image Reconstruction

  • The concept of projections in CT.
  • Introduction to Radon transforms and inversion.
  • Mathematical framework for image reconstruction from projections.

• Image Reconstruction Algorithms: Basic Concepts

  • Overview of common image reconstruction methods.
  • Filtered backprojection: Concept, derivation, and applications.
  • Iterative reconstruction methods (e.g., EM algorithm, Kaczmarz method).

• Filtering and Backprojection

  • How filtering is used to enhance projections.
  • Step-by-step development of the filtered backprojection algorithm.
  • Practical aspects of the backprojection in CT imaging.

• Iterative Methods for Image Reconstruction

  • Introduction to iterative reconstruction algorithms.
  • Convergence properties of iterative methods.
  • Algebraic Reconstruction Techniques (ART).
  • Simultaneous Iterative Reconstruction Technique (SIRT).

• Advanced Techniques in Image Reconstruction

  • Fourier-based reconstruction methods.
  • Use of sinogram and its relationship to Fourier transforms.
  • Total Variation (TV) minimization and its role in noise reduction.
  • Nonlinear reconstruction techniques.

• Resolution and Artifacts in CT Imaging

  • Types of artifacts that can appear in CT images (e.g., ring artifacts, beam hardening).
  • Methods for artifact reduction and image correction.
  • Effects of spatial resolution and contrast resolution on image quality.

• 3D Reconstruction and Volumetric Imaging

  • Principles of 3D reconstruction from 2D projections.
  • Volume rendering techniques.
  • The use of CT in 3D modeling and visualization.

• Advanced Applications in CT Imaging

  • Use of CT in specialized fields (e.g., cardiology, oncology).
  • Functional CT and the integration with other imaging modalities.
  • Dual-energy CT and its potential advantages.

• Performance Evaluation and Quality Assurance

  • Methods for assessing the performance of reconstruction algorithms.
  • Evaluation metrics for image quality (e.g., contrast-to-noise ratio, signal-to-noise ratio).
  • Practical aspects of system calibration and quality control.

• Future Directions and Challenges in CT Reconstruction

  • Emerging techniques in deep learning and AI-based reconstruction methods.
  • Ongoing challenges in speed, accuracy, and radiation dose reduction.
  • Innovations in real-time reconstruction and adaptive systems.

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