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Books, Free Shipping, Medical Image Reconstruction A Conceptual Tutorial

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Product Description:

Medical Image Reconstruction A Conceptual Tutorial introduces the classical and

modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with/o-minimization are also included.

This book is written for engineers and researchers in the field of biomedical engineering specializing in medical imaging and image processing with image reconstruction.


1 Basic Principles of Tomography

1.1 Tomography

1.2 Projection

1.3 Image Reconstruction

1.4 Backprojection

1.5 Mathematical Expressions

1.6 Worked Examples

1.7 Summary



2 Parallel-Beam Image Reconstruction

2.1 Fourier Transform

2.2 Central Slice Theorem

2.3 Reconstruction Algorithms

2.4 A Computer Simulation

2.5 ROI Reconstruction with Truncated Projections

2.6 Mathematical Expressions

2.7 Worked Examples

2.8 Summary



3 Fan-Beam Image Reconstruction

3.1 Fan-Beam Geometry and Point Spread Function

3.2 Parallel-Beam to Fan-Beam Algorithm Conversion

3.3 Short Scan

3.4 Mathematical Expressions

3.5 Worked Examples

3.6 Summary



4 Transmission and Emission Tomography

4.1 X-Ray Computed Tomography

4.2 Positron Emission Tomography and Single Photon Emission Computed Tomography

4.3 Attenuation Correction for Emission Tomography

4.4 Mathematical Expressions

4.5 Worked Examples

4.6 Summary



5 3D Image Reconstruction

5.1 Parallel Line-Integral Data

5.2 Parallel Plane-Integral Data

5.3 Cone-Beam Data

5.4 Mathematical Expressions

5.5 Worked Examples

5.6 Summary



6 Iterative Reconstruction

6.1 Solving a System of Linear Equations

6.2 Algebraic Reconstruction Technique

6.3 Gradient Descent Algorithms

6.4 Maximum-Likelihood Expectation-Maximization Algorithms

6.5 Ordered-Subset Expectation-Maximization Algorithm

6.6 Noise Handling

6.7 Noise Modeling as a Likelihood Function

6.8 Including Prior Knowledge

6.9 Mathematical Expressions

6.10 Reconstruction Using Highly Undersampled Data with 10 Minimization

6.11 Worked Examples

6.12 Summary



7 MRI Reconstruction

7.1 The \"M\"

7.2 The \"R\"

7.3 The \"T\"

7.4 Mathematical Expressions

7.5 Worked Examples

7.6 Summary




Product Details

Author Zeng Gengsheng

Publisher Higher Education Press

Isbn 9787040204377

Published November 2009

Pages 198

Size 16K

Edition First

Format Hardcover

Language English

Page material gelatine plate paper

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