1 Challenge the future Modeling Electromagnetic Fields in Strongly Inhomogeneous Media An...

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1 Challenge the future Modeling Electromagnetic Fields in Strongly Inhomogeneous Media An Application in MRI Kirsten Koolstra, September 24 th , 2015

Transcript of 1 Challenge the future Modeling Electromagnetic Fields in Strongly Inhomogeneous Media An...

Page 1: 1 Challenge the future Modeling Electromagnetic Fields in Strongly Inhomogeneous Media An Application in MRI Kirsten Koolstra, September 24 th, 2015.

1Challenge the future

Modeling Electromagnetic Fields in Strongly Inhomogeneous MediaAn Application in MRIKirsten Koolstra, September 24th, 2015

Page 2: 1 Challenge the future Modeling Electromagnetic Fields in Strongly Inhomogeneous Media An Application in MRI Kirsten Koolstra, September 24 th, 2015.

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IntroductionMagnetic Resonance Imaging (MRI)

www.neurensics.com/technische-specificaties

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Introduction

𝐵0=1.5T

RF Interference in MRI

𝜆∝1𝐵0

𝐵0=3.0T

Brink et al., JMRI (2015)

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IntroductionThe Effect of Dielectric Pads

De Heer et al., Magn Res Med (2012)

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Introduction

Without pad With pad

With padWithout pad

The Effect of Dielectric Pads

De Heer et al., Magn Res Med (2012)

Brink et al., Invest Rad (2014)

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IntroductionDesign Procedure: Numerical Modeling

Brink and Webb, Magn Res Med (2013)

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Challenges

• Strong (localized) inhomogeneities in medium parameters

• Large computational domain due to the body model

• Accurate for low resolution!

• Fast!

• Take into account the boundary conditions

In Numerical Modeling

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Goal

Obtain a solution that is

1. accurate

2. obtained within short computation time

Approach:

• Compare different discretization schemes for a simple test case

• Compare two iterative solvers, GMRES and IDR(s), to solve the discretized system

• Verify the results by performing human body simulations

Page 10: 1 Challenge the future Modeling Electromagnetic Fields in Strongly Inhomogeneous Media An Application in MRI Kirsten Koolstra, September 24 th, 2015.

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The Volume Integral Equation

𝐄=𝐄 inc+(kb2+𝛻𝛻 ∙)𝐒 ( 𝜒 𝑒𝐄 )

𝐒( 𝐉)=∫Ω

𝑔 (𝐱 ′ −𝐱 ) 𝐉 (𝐱 )d 𝐱

𝐄 inc

𝐄sc

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Different Formulations

EVIE:

DVIE:

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The Volume Integral Equation

𝐄 inc=𝐄− (kb2+𝛻𝛻 ∙)𝐒 ( 𝜒𝑒𝐄)

[𝐸𝑥i nc

𝐸𝑦i nc ]=[𝐸𝑥

𝐸 𝑦 ]− (kb2+𝛻𝛻 ∙) [𝑆𝑥(𝜒 𝑒𝐸𝑥)𝑆𝑦 (𝜒 𝑒𝐸 𝑦)]

2𝐷

• The - and -components of the electric field are coupled via the operator.

• The vector potential depends on the material parameters.

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The Method of Moments

1 2 3 4

𝑛

5

6

1 2 3 4

𝑛

5

6

𝐴𝐱=𝐛ℒ𝑢= 𝑓

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The Method of MomentsApproximation of a Function

1 2 3 4 5 6 7 8 9

𝑓 (𝑥)

𝑥𝑖

𝑓 (𝑥 )=∑𝑖=1

9

𝑓 𝑖𝜑𝑖(𝑥 )

1. Specify

2. Find for all

3. Reconstruct

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The Method of Moments

[𝐸𝑥i nc

𝐸𝑦i nc ]=[𝐸𝑥

𝐸 𝑦 ]− (kb2+𝛻𝛻 ∙) [𝑆𝑥(𝜒 𝑒𝐸𝑥)𝑆𝑦 (𝜒 𝑒𝐸 𝑦)]

Expansions

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The Method of Moments

[𝐸𝑥i nc

𝐸𝑦i nc ]=[𝐸𝑥

𝐸 𝑦 ]− (kb2+𝛻𝛻 ∙) [𝑆𝑥(𝜒 𝑒𝐸𝑥)𝑆𝑦 (𝜒 𝑒𝐸 𝑦)]

Expansions

is solved via expanding

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The Method of Moments

[𝐸𝑥i nc

𝐸𝑦i nc ]=[𝐸𝑥

𝐸 𝑦 ]− (kb2+𝛻𝛻 ∙) [𝑆𝑥(𝜒 𝑒𝐸𝑥)𝑆𝑦 (𝜒 𝑒𝐸 𝑦)]

Expansions

is solved via expanding

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The Method of Moments

[𝐸𝑥i nc

𝐸𝑦i nc ]=[𝐸𝑥

𝐸 𝑦 ]− (kb2+𝛻𝛻 ∙) [𝑆𝑥(𝜒 𝑒𝐸𝑥)𝑆𝑦 (𝜒 𝑒𝐸 𝑦)]

Expansions

[𝒆𝒙

𝒆𝒚 ]=[𝒃𝒙

𝒃𝒚 ]• How do we incorporate the operator in the matrix ?

• How do we deal with the derivative terms?

𝐴𝛻𝛻 ∙𝐒=[ 𝜕

𝜕 𝑥𝜕𝜕𝑥

𝑆𝑥+𝜕𝜕 𝑥

𝜕𝜕 𝑦

𝑆 𝑦

𝜕𝜕 𝑦

𝜕𝜕𝑥

𝑆𝑥+𝜕𝜕 𝑦

𝜕𝜕 𝑦

𝑆𝑦 ]

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The Method of MomentsFast Fourier Transform

Remember,

𝐒(𝜒𝑒𝐄)(𝐱′ )=∫Ω

𝑔 (𝐱′−𝐱 ) 𝜒𝑒(𝐱)𝐄 (𝐱 )d 𝐱¿𝑔∗ 𝜒𝑒𝐄

¿ℱ {𝑔}ℱ {𝜒𝑒𝐄 }ℱ {𝐒 }=ℱ {𝑔∗ 𝜒 𝑒𝐄 }And

⟹𝐒=ℱ− 1 {ℱ {𝑔 }ℱ {𝜒𝑒𝐄} } .

So, use fast Fourier transform (FFT) algorithms to incorporate in the matrix !

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The Method of Moments

[𝐸𝑥i nc

𝐸𝑦i nc ]=[𝐸𝑥

𝐸 𝑦 ]− (kb2+𝛻𝛻 ∙) [𝑆𝑥(𝜒 𝑒𝐸𝑥)𝑆𝑦 (𝜒 𝑒𝐸 𝑦)]

Expansions

[𝒆𝒙

𝒆𝒚 ]=[𝒃𝒙

𝒃𝒚 ]• How do we incorporate the operator in the matrix ?

• How do we deal with the derivative terms?

𝐴𝛻𝛻 ∙𝐒=[ 𝜕

𝜕 𝑥𝜕𝜕𝑥

𝑆𝑥+𝜕𝜕 𝑥

𝜕𝜕 𝑦

𝑆 𝑦

𝜕𝜕 𝑦

𝜕𝜕𝑥

𝑆𝑥+𝜕𝜕 𝑦

𝜕𝜕 𝑦

𝑆𝑦 ]

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The Method of Moments

𝑥 𝑦

𝑥𝑦

Basis Functions: Rooftop 𝐸𝑥 (𝒙 )=∑𝑖=1

𝑛

𝑒𝑖𝑥𝜓 𝑖

𝑥 (𝒙 )

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The Method of Moments

[𝐸𝑥i nc

𝐸𝑦i nc ]=[𝐸𝑥

𝐸 𝑦 ]− (kb2+𝛻𝛻 ∙) [𝑆𝑥(𝜒 𝑒𝐸𝑥)𝑆𝑦 (𝜒 𝑒𝐸 𝑦)]

Expansions

[𝒆𝒙

𝒆𝒚 ]=[𝒃𝒙

𝒃𝒚 ]• How do we incorporate the operator in the matrix ?

• How do we deal with the derivative terms?

𝐴𝛻𝛻 ∙𝐒=[ 𝜕

𝜕 𝑥𝜕𝜕𝑥

𝑆𝑥+𝜕𝜕 𝑥

𝜕𝜕 𝑦

𝑆 𝑦

𝜕𝜕 𝑦

𝜕𝜕𝑥

𝑆𝑥+𝜕𝜕 𝑦

𝜕𝜕 𝑦

𝑆𝑦 ]

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Central Difference SchemesOn staggered and non-staggered grids

Non-staggered grid Staggered grid

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𝑚 ,𝑛𝑚 ,𝑛

Central Difference SchemesOn staggered and non-staggered grids

Non-staggered grid Staggered grid

𝑚 ,𝑛

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Benchmark Problem

• TE-polarization

• Plane wave incident field

• Muscle/fat tissue

Scattering on a Two-Layer Conducting Cylinder

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Recap

• Equations:

• Method:

• Benchmark Problem:

The Ingredients

Model

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ResultsScattering on a Two-Layer Conducting Cylinder

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ResultsComparison of EVIE and DVIE

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ResultsScattering on a Two-Layer Conducting Cylinder

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Scattering on a Circle vs Square

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Results

Circle Square

Scattering on a Circle vs on a Square

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Central Difference Schemes

StaggeredNon-Staggered

2n

d o

rder

schem

e4

th o

rder

schem

e

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ResultsGlobal Error Propagation

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Error Reduction

Original With smoothing

Smoothing the Contrast

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Ori

gin

al

Sm

ooth

ed

ResultsThe Effect of Smoothing the Contrast

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Original With smoothing

ResultsThe Effect of Smoothing along the Axes

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Overview

ℒ𝑢= 𝑓 A 𝐱=𝐛 𝐱

𝐱𝑖+1=𝐱 𝑖+𝛂𝑖

Method of

Moments

IterativeSolver

Finding a Solution

?

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Comparison of GMRES and IDR(s)

Properties of the Iterative Solver

𝑛=¿

𝑖=¿iteration number

number of unknowns

GMRES IDR(s)

Iterations until convergence

Work per iteration

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Comparison of GMRES and IDR(s)

Properties of the Iterative Solver

𝑛=¿

𝑖=¿iteration number

number of unknowns

GMRES IDR(s)

Iterations until convergence

Work per iteration

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Comparison of GMRES and IDR(s)

Properties of the Iterative Solver

𝑛=¿

𝑖=¿iteration number

number of unknowns

GMRES IDR(s)

Iterations until convergence

Work per iteration

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Results

GMRES IDR(s)

Comparison of GMRES and IDR(s)

Page 42: 1 Challenge the future Modeling Electromagnetic Fields in Strongly Inhomogeneous Media An Application in MRI Kirsten Koolstra, September 24 th, 2015.

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Human Body SimulationsScattering on a Human Body with Dielectric Pad

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Human Body Simulations

High resolution

Staggered grid Non-staggered grid

Comparison of the staggered and non-staggered grid

Low resolution Low resolution

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Conclusions

• Factors that influence the accuracy are the geometry and the mixed derivative terms.

• Smoothing improves the geometrical inaccuracies with the cost of computation time.

• The mixed derivative term has a large effect on the accuracy and is best approximated on a staggered grid.

• IDR(s) reduces the computation time considerably.

• Human body simulations are in agreement with the cylider test case simulations: the DVIE method on a staggered grid results in the most accurate solution on low resolution.

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AbstractModeling electromagnetic fields in MRI involves two

main challenges: the solution has to be accurate and it

has to be obtained within short computation time.

The method of moments is used to discretize different

formulations of the volume integral equation

corresponding to Maxwell's equations.

The good performance of a staggered grid with respect

to a non-staggered grid shows that the way of treating

the mixed derivative terms is of great importance.

The performance of a higher order derivative scheme

on a non-staggered grid is close to the performance of

a staggered grid.

IDR(s) shows excellent performance in reducing the

computation time that is obtained with GMRES.

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Function Spaces

EVIE: DVIE: JVIE:

where

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Simulation Parameters

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Computation Times

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Convergence

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Contrast Dependence

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Smoothing the Contrast

𝜀𝑚 ,𝑛= ∑𝑅 (𝑚 ,𝑛 )

116

𝜀𝑝 ,𝑞

A Matlab Filter

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The Electric Fields

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The Electric Fields

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Scattering on a Two-Layer CylinderLow Resolution Results

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The Electric FieldsScattering on a Square-Shaped Object