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Leweke, Sarah: The inverse magneto-electroencephalography problem for the spherical multiple-shell model : theoretical investigations and numerical aspects. 2018
Inhalt
Zusammenfassung
Abstract
Contents
Introduction
Basics
Preliminaries
Notation
Jacobi and Legendre Polynomials
Vector Calculus in Spherical Geometries
Scalar Spherical Harmonics
Definition of Spherical Harmonics
Inner and Outer Harmonics
Theory of Distributions
Modelling the Magnetoencephalography Problem
Modelling the Electroencephalography Problem
Solving the Direct Problem
Preliminaries
Orthonormal Systems on the Interval
Vector Spherical Harmonics
Definition of Vector Spherical Harmonics
Orthogonality and Completeness of Vector Spherical Harmonics
Harmonicity of Vector Spherical Harmonics
Decomposition of via Vector Spherical Harmonics
Vector Legendre Polynomials
Vector Outer Harmonics
Orthonormal Systems on the Ball
Vector Legendre-type Integral Kernels
Definition and Well-definedness
Examples: Magneto-electroencephalography Kernels
Further Properties
Vector Legendre-type Integral Operators
Definition of the Integral Operators
Continuity and Differentiability of the Potential
Solution of the Direct Problem
A Harmonic Vector Legendre-type Integral Operator
Definition
Harmonicity of the Kernel and Potential
Direct Magnetoencephalography Problem
Measurements from Magnetometers
Measurements from Gradiometers
Direct Electroencephalography Problem
Solving the Inverse Problem
Introduction to Inverse Problems
Ill-Posedness of the VLI Problem
Continuous and Star-shaped Problem
Harmonic VLI Problem
Uniqueness Constraints for the Continuous VLI Problem
Radial Uniqueness Constraints
Directional Uniqueness Constraints
Inverse Magneto-electroencephalography Problem
Non-uniqueness
Instability
Existence of a Solution
Additional Uniqueness Constraints
Scalar General Integral Problem
Scalar Continuous VLI Operator
Previous Scalar Approaches for the Magneto-encephalography Problem
Hodge Decomposition
Hodge Decomposition for MEG
Hodge Decomposition for EEG
Morse-Feshbach Vector Approach
Morse-Feshbach Approach for MEG
Morse-Feshbach Approach for EEG
Helmholtz Representation
Helmholtz Decomposition for MEG
Helmholtz Decomposition for EEG
Regularization
Preliminaries
Sobolev Spaces on the Ball
Definition and Basic Properties
Reproducing Kernel Hilbert Spaces on the Ball
Basics of Regularization Methods
Parameter Choice Methods
Regularized Functional Matching Pursuit Algorithm
Algorithm and Properties
Regularized Functional Matching Pursuit Algorithm for Simultaneous Inversion
Regularized Orthogonal Functional Matching Pursuit Algorithm
Numerical Solution of the MEG and EEG Problem
Synthetic Test Case
Synthetic Test Current
Synthetic Data
Foundation for Implementation
The Dictionaries
The Preprocessing
The Visualization
Other Reconstruction Methods
Regularized Ritz Method
Scalar Spline Method
Scalar Splines
Scalar Splines for the MEG Problem
Scalar Synthetic Test Current
Corresponding Vector-Valued Neuronal Current
Scalar Splines for the EEG Problem
Vector Spline Method
Numerical Results
Regularized (Orthogonal) Functional Matching Pursuit
Performance Benchmark
Evaluation of Parameter Choice Methods
Regularized Ritz Method
Scalar Splines
Scalar Splines for MEG
Scalar Splines for EEG
Vector Splines for EEG
Comparison of the Numerical Methods
Inversion of Real Data
Final Remarks
Conclusion and Outlook
Appendix
Supplementary Calculations for the MEG Gradiometer
List of Figures
List of Tables
Bibliography