Presenter: Yang-Min Huang
Adviser: Dr. Ji-Jer Huang
Chairman: Hung-Chi Yang
2013/4/10
Electrical Impedance Tomography ：電阻抗斷層造影
1
Outline
 Introduction
 Paper review
 Motivations & Purposes
 Methods & Materials
 Result
 Future Works
 References
2
Introduction
 Electrical impedance tomography (EIT)
• Injection current sources
• Measurement voltages
• Image reconstruction
EIT：電阻抗斷層造影
3
Introduction
 Comparison of Imaging Techniques
Imaging
Imaging
Cost($)
Resolution(%)
MRI
Structural
Functional
Highest
<0.1
X-ray CT
Structural
PET
Ultrasound
Advantages
Disadvantages
Soft-tissue, High resolution
Expensive, Magnetic field
Technique
EIT
limit
Radiation, Difficult to
distinguish the soft-tissue
High
<1
High resolution, Fast
Functional
Middle
>3
Ration show the organs
physiological function
Low resolution, Radiation
Structural
Functional
1
Non-invasive, Fast
Low resolution, High noise,
Low
Functional
Lowest
Bone reflect
1
Non-invasive, No radiation,
Low resolution
Portable
MRI：核磁共振造影
X-ray CT：X光電腦斷層
PET：正子放射造影
Ultrasound：超音波
EIT：電阻抗斷層造影
4
Paper review(1)
 From:Do˘ga G¨ursoy*, Member, IEEE, Yasin Mamatjan, Andy Adler, and Hermann
Scharfetter” Enhancing Impedance Imaging Through Multimodal Tomography”
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 58, NO. 11,
NOVEMBER 2011
 Purpose
To investigate how much additional performance
improvements can be expected by combining datasets of
different modalities.
EIT：電阻抗斷層造影 MIT：磁感應斷層造影 ICEIT：誘導電流電阻抗斷層造影
5
Paper review(1)
 Electrode configuration
6
Paper review(1)
7
Motivations & Purposes
 To get the real image for using FEM and Neural
Network.
 To complete the algorithm for using Matlab.
8
Methods & Materials
 Poisson equation
 Algorithm
The forward problem
The inverse problem
9
Methods & Materials
 Poisson equation
σ：導電係數
Ĵ : 電流密度
n：物體表面的法向量
10
Methods & Materials
 FEM for EIT forward problem
Galerkin method
Φ：voltage
V：basis vector space
σ：conductivity
FEM：有限元素法
EIT：電阻抗斷層造影
Galerkin method：伽遼金方法
11
Methods & Materials
 Radial Basis Function(RBF) neural network
RBF neural network ：輻狀基底函數類神經網路
σ：變異數
SN ：樣本總數
12
Methods & Materials
 Block diagram
13
電壓比較
電流比較
3
1.5
2
1
1
0.5
電流
電壓
0
0
-1
Result
-2
-3
-4
0
5
10
15
20
25
節點編號
30
35
40
-0.5
-1
-1.5
26
45
28
30
32
34
節點編號
36
38
40
 Verification
Sample
4
2
1.8
3
1.6
2
1.4
1
1.2
0
1
0.8
-1
0.6
-2
0.4
-3
-4
-4
0.2
-3
-2
-1
0
1
2
3
4
0
14
42
Result
 Measured voltage for using different current, 15 train
data
Sample
4
Image Reconstruction
1000
900
3
Sample
4
1000
900
3
800
2
2
600
0
500
400
-1
1
600
0
500
400
-1
-4
-4
100
-3
-2
-1
0
1
2
3
-4
-4
4
-3
-2
Sample
1000
900
3
-1
0
1
2
3
2
1000
900
3
600
0
500
400
-1
1
600
0
500
400
-1
100
1
2
3
4
-3
-800
-3
-2
-1
0
1
2
3
4
-3
100
-2
-1
0
1
-200
-400
-600
-3
-1000
-4
-4
1000
4
-800
-3
-2
-1
2
3
4
0
1
2
3
4
900
3
1000
900
3
800
800
2
700
1
600
0
500
400
-1
700
1
600
0
500
400
-1
300
300
-2
200
-3
-4
-4
-1000
Sample
4
-2
-3
0
-1
-2
200
-4
-4
200
0
-600
300
200
-3
400
1
-400
2
-2
0
-200
-1
700
300
-2
-1
0
800
2
1
600
Sample
4
700
-2
0
-4
-4
4
800
-3
200
Image Reconstruction
4
-4
-4
1
-2
100
800
2
200
-3
1000
3
400
300
-2
4
600
2
200
-3
800
3
700
300
-2
1000
800
700
1
Image Reconstruction
4
100
-3
-2
-1
0
1
2
3
4
200
-3
-4
-4
100
-3
-2
-1
0
1
2
3
4
15
Future Works
 Paper review
 To simulate more samples of image pattern
 To improve the RBF neural network
 To complete the user interface
16
References
 P. Wang, H. Li, L. Xie, Y. Sun, “The Implementation of FEM and RBF Neural
Network in EIT”, Proceedings of the 2009 Second International Conference on
Intelligent Networks and Intelligent Systems, pp. 66-69, IEEE Computer
Society, 2009.
 Do˘ga G¨ursoy*, Member, IEEE, Yasin Mamatjan, Andy Adler, and Hermann
Scharfetter” Enhancing Impedance Imaging Through Multimodal Tomography”
IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, VOL. 58, NO.
11, NOVEMBER 2011
 Ybarra, G. A., Q. H. Liu, G. Ye, K. H. Lim, R. George, and W. T. Joines, "Breast
imaging using electrical impedance tomography (EIT)," Emerging Technologies
in Breast Imaging and Mammography, Ed.: J. Suri, R. M. Rangayyan, and S.
Laxminarayan, American Scientific Publishers, 2008.
 黃俊惟，電阻抗斷層成像技術之研究，南台科技大學電機工程研究所碩士
論文，2010
17