Automatic Generation of Volume Conductor Models … · Automatic Generation of Volume Conductor Models of the Human ... SCT CoB CaB CSF ... Automatic Generation of Volume Conductor

Automatic Generation of VolumeConductor Models of the HumanHead for EEG Source Analysis

Benjamin LanferWWU Munster / BESA GmbH

BaCI 2015

EEG Source Analysis and Volume Conductor Models

FEM (BEM, FDM, ...) solution ofquasi-static Maxwell equations

Volume conductormodel

Inverse Problem

Forward Problem

B. Lanfer ([email protected]) 1 / 13

Generation of Individual, Realistic Head Models


What Do We Know About the Segmentation?

A-priori Knowledge

I Exploiting a-priori knowledge about . . .I . . . arrangment of head tissuesI . . . occurence of tissues at locations relative to (anatomical) reference

surfaces


Segmentation in a Bayesian Framework

I Bayesian a-posteriori probability as measure for good segmentation

P (x |y) ∝ l(y |x)︸︷︷︸Likelihood

P (x)︸︷︷︸A-priori Probability

I Likelihood: how well does the current segmentation explain theobserved image?

l(yi |xi, λc) =1√

(2π)k|Σc|exp

{−1

2(yi − µc)

ᵀΣ−1c (yi − µc)

}


The Markov Random Field Model


The Markov Random Field Model (cont.)

I Markov Random Field (MRF)

P(xi |xS\{i}

)= P (xi |xNi) Markovianity

I Each MRF is equivalent to a Gibbs Random Field

P (x) =2

Zexp

(− 1

TU(x)

)Gibbs distribution


The Markov Random Field Model (cont.)

I Gibbs energy function as a sum of single-site and pairwise cliquepotentials V1, resp., V2

U(x) =∑i∈S

V1(i, xi) +∑i∈S

∑i′∈Ni

V2(i, i′, xi, xi′

)+ . . .

I Definition of pairwise clique potentials using pseudo transitionprobabilities Pxi,xi′ (i, i

′)

V2(i, i′, xi, xi′) = − ln

(Pxi,xi′ (i, i

′))

BGSkin /Muscle

SCT

CoB

CaB

CSF

Dura

GM WM


The Atlas-Based A-priori Probability


Atlas Generation and Projection

I 20 labeled, template images from BrainWeb database1

I Averaging and normalization of local tissue histograms

I Atlas: local tissue probability mass functions depending on distancesto reference surfaces

I Projection to individual reference surfaces

Template image Local histogram

1Aubert-Broche et al., NeuroImage, 2006

Atlas Generation and Projection

I 20 labeled, template images from BrainWeb database1

I Averaging and normalization of local tissue histograms

I Atlas: local tissue probability mass functions depending on distancesto reference surfaces

I Projection to individual reference surfaces

Individual MRI and reference surfaces Local probability mass function

1Aubert-Broche et al., NeuroImage, 2006

The Segmentation Algorithm

Validation vs. Manual Raters

... ... ......

Proposedapproach

Majority

vote

Averaging


Results Validation vs. Manual Raters


Summary and Outlook

Summary

I Accurate segmentation of the four most relevant tissues for EEGsource analysis

I Low effort enables wider application of individual, realistically shapedFEM models in EEG source analysis, tDCS simulations, . . .

Outlook

I Improved segmentation of the skull base and the facial skull, e.g.,using templates

I Important for high-density electrode caps, temporal lobe activity

I Treatment of pathological anatomies (lesions, skull trepanation holes)


Thank you!

WWU / IBB

I PD Dr. Carsten H. Wolters

I Prof. Dr. Martin Burger

I Prof. Dr. Christo Pantev

I Umit Aydin

I Felix Lucka

I Johannes Vorwerk

I Sven Wagner

I Dr. Harald Kugel

BESA GmbH

I Dr. Michael Scherg

I Dr. Tobias Scherg

I Theo Scherg

Documents

Automatic Generation of Volume Conductor Models … · Automatic Generation of Volume Conductor Models of the Human ... SCT CoB CaB CSF ... Automatic Generation of Volume Conductor