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Handbook of Mathematical Methods in Imaging

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Cover of 'Handbook of Mathematical Methods in Imaging'

Table of Contents

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    Book Overview
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    Chapter 1 Linear Inverse Problems
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    Chapter 2 Large-Scale Inverse Problems in Imaging
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    Chapter 3 Regularization Methods for Ill-Posed Problems
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    Chapter 4 Distance Measures and Applications to Multimodal Variational Imaging
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    Chapter 5 Energy Minimization Methods
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    Chapter 6 Compressive Sensing
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    Chapter 7 Duality and Convex Programming
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    Chapter 8 EM Algorithms
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    Chapter 9 Iterative Solution Methods
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    Chapter 11 Level Set Methods for Structural Inversion and Image Reconstruction
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    Chapter 12 Sampling Methods
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    Chapter 14 Electrical Impedance Tomography
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    Chapter 16 Tomography
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    Chapter 21 Optical Imaging
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    Chapter 22 Supervised Learning by Support Vector Machines
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    Chapter 23 Total Variation in Imaging
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    Chapter 24 Numerical Methods and Applications in Total Variation Image Restoration
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    Chapter 25 Mumford and Shah Model and Its Applications to Image Segmentation and Image Restoration
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    Chapter 26 Local Smoothing Neighborhood Filters
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    Chapter 27 Neighborhood Filters and the Recovery of 3D Information
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    Chapter 28 Splines and Multiresolution Analysis
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    Chapter 34 Starlet Transform in Astronomical Data Processing
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    Chapter 35 Differential Methods for Multi-dimensional Visual Data Analysis
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    Chapter 36 Microlocal Analysis in Tomography
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    Chapter 37 Sonic Imaging
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    Chapter 38 Optical Flow
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    Chapter 39 Non-linear Image Registration
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    Chapter 40 Image Segmentation with Shape Priors: Explicit Versus Implicit Representations
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    Chapter 41 Imaging in Random Media
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    Chapter 43 Mathematics of Electron Tomography
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    Chapter 44 Mathematical Modelling of Optical Coherence Tomography
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    Chapter 45 Mathematical Methods in PET and SPECT Imaging
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    Chapter 46 EM Algorithms from a Non-stochastic Perspective
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    Chapter 47 Expansion Methods
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    Chapter 48 Inverse Scattering
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    Chapter 49 Synthetic Aperture Radar Imaging
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    Chapter 50 Photoacoustic and Thermoacoustic Tomography: Image Formation Principles
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    Chapter 51 Mathematics of Photoacoustic and Thermoacoustic Tomography
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    Chapter 52 Wave Phenomena
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    Chapter 53 Statistical Methods in Imaging
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    Chapter 54 Gabor Analysis for Imaging
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    Chapter 55 Shape Spaces
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    Chapter 56 Variational Methods in Shape Analysis
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    Chapter 57 Manifold Intrinsic Similarity
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Title
Handbook of Mathematical Methods in Imaging
Published by
Springer New York, May 2015
DOI 10.1007/978-1-4939-0790-8
ISBNs
978-1-4939-0789-2, 978-1-4939-0790-8
Editors

Scherzer, Otmar

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The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 19 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 5 26%
Student > Master 3 16%
Student > Bachelor 2 11%
Student > Ph. D. Student 2 11%
Student > Doctoral Student 2 11%
Other 1 5%
Unknown 4 21%
Readers by discipline Count As %
Physics and Astronomy 3 16%
Engineering 2 11%
Materials Science 2 11%
Psychology 1 5%
Earth and Planetary Sciences 1 5%
Other 4 21%
Unknown 6 32%