臺灣博碩士論文加值系統

電阻抗影像系統具有非侵入式、價格低廉、長期監測以及無輻射性傷害等優點，在工業與醫療方面逐漸廣泛受到重視與應用。目前電阻抗影像重建技術有很多方法被研發出來，但是這些方法中有好的解析度者通常需要花費較長的計算時間，有快速重建演算法卻往往解析度較差，因此本論文係研發一套能兼顧解析度與運算時間且能獨立運作之電阻抗影像重建；主要目的是應用數位處理系統(TI TMS320C6713)實現三角函數電流圖型之等電位逆投射法，以重建電阻抗影像。首先使用有限元素法計算出電阻抗影像系統之培養皿內部等均質之電位線分布，然後建立電極電位差與內部區域電阻係數線性關係，利用表面電極所測得電位差，將電阻係數影像疊加重建出來。實驗是使用兩種電流圖型，在不同雜訊與物體大小，以有限元素法模擬出培養皿邊界之電壓值，重建出影像加以比較。實驗結果發現，使用三角函數電流圖所重建之內部中心物體影像解析度為半徑0.0125公分，而相鄰對電流圖型則為半徑0.0225公分，本研究所提出之系統有較佳解析度；在加入達1%的高斯雜訊時，模擬物體擺放中央的狀況，本系統仍可重建出影像，因此本系統也有較佳的抗雜訊功能。另外本研究系統的所花費運算時間與一般逆投射重建演算法一樣，重建速度也相當快速。綜合而言，本研究提出一套以DSP為基礎之硬體實現演算法，具有獨立運作與快速重建功能，其中也開發了一套人機介面，以簡化使用流程。

Electrical impedance tomography has the advantages of non-invasiveness, low cost, long-term use, and no radiation hazard. It attracts lots of attentions and is widely applied in the industry and medicine. Currently, there are many image reconstruction methods proposed and developed for EIT. Nevertheless, some of these methods may produce good image resolution, but may take long computation time. Some methods may be fast in image reconstruction, but may produce bad image quality. Therefore, the purpose of this study is to develop a stand alone image reconstructor that may have good image resolution as well as short computation time. A DSP (TI TMS320C6713) is employed as the kernel to realize the filtered backprojection based on the equi-potential lines using rotating sinusoidal current patterns. Firstly, the distribution of the equi-potential lines for sinusoidal current pattern of homogeneous phantom is computed using the finite element method. Secondly, the linear relationship between the inside region and electrode pair with the same equi-potential line is found and saved as the look-up-table. According to the measured voltage difference on the surface electrodes, the resistivity image can be reconstructed using the backprojection method. The distance between the pixel and electrode-pair is used the weight as the spatial filter. Both the sinusoidal current pattern and adjacent current pattern are applied to the phantom containing different size of targets and are added with 1% of Gaussian noise level. Using the finite element model for simulating the culture dish, their corresponding boundary voltage patterns may then computed for impedance image reconstruction. From the experimental results, it is shown that the smallest distinguishable centered targets are 0.0125 cm, and 0.0225 cm in diameter for sinusoidal current pattern and adjacent current pattern, respectively. For the centered target with 1% Gaussian noise added, the proposed image reconstructor still can reconstruct the impedance image. So, it is well immune to the noise. Besides, this reconstrutor spends the same computation time as that for traditional backprojection method. Thus, the proposed system is also fast in impedance image reconstruction. Above all, the proposed impedance image reconstructor has the merits of stand-alone operation and fast image reconstruction. In addition, a friendly graphical user interface (GUI) is also designed and implemented to ease the operation.

CHINESE ABSTRACT ………………………………………Ⅳ
ABSTRACT……………Ⅴ
ACKNOWLEDGMENT ……………………………………Ⅵ
LIST OF TABLES……………………Ⅸ
LIST OF FIGURES …………………………Ⅹ

Chapter 1 Introduction …………………1
1.1 Electrical Impedance Tomography…………………………1
1.2 Current Patterns………………2
1.2.1 Adjacent-Pair Current Patterns………………………………2
1.2.2 Opposite-Pair Current Patterns……………………………………3
1.2.3 Adaptive Current Patterns………………3
1.3 Reconstruction Algorithm……………4
1.3.1 NOSER …………………………4
1.3.2 Backprojection …………………………4
1.4 Literature Review………………5
1.5 Motivations and Purposes ………………7

Chapter 2 Materials and Methods ……………8
2.1 EIT System Description………………………8
2.2 Research Framework …………………………8
2.3 Equi-potential Lines Computation…………9
2.3.1 Sinusoidal Current Pattern.……………9
2.3.2 Finite Element Model Development……10
2.3.3 Equi-potential Lines Computation ………11
2.4 Filtered Backprojection ………………13
2.4.1 Forward and Inverse Problem………………13
2.4.2 Filtered Backprojection ……………………14
2.5 System Development………………18
2.5.1 DSP Description ………………18
2.5.2 Software Implementation………………19

Chapter 3 Simulation Experiments and Results………………22
3.1 Equi-potential Lines Mapping………………22
3.2 Filtered Backprojection……………………24
3.2.1 Voltage Computation ………………24
3.2.2 Reconstruction Algorithm……………26
3.3 DSP Realization…………………36
3.3.1 The Data Analysis……………………36
3.4 Graphic user interface design and System Testing…………………39

Chapter 4 Discussions …………………………41

Chapter 5 Conclusions and Prospects ……………45
5.1 Conclusions ………………………45
5.2 Prospects ………………………45

References…………46

[1] R. Chassaing, DSP Applications Using C and the TMS320C6X DSK. USA: John Wiley & Sons, Inc., 2002.
[2] R. Chassaing, Digital Signal Processing and Applications with the C6713 and C6416 DSK. USA: John Wiley & Sons, Inc., 2005.
[3] E. Demidenko, A. Hartov, N. Soni, and K. D. Paulsen, “On optimal current patterns for electrical impedance tomography,” IEEE Trans. Biomed. Eng., vol.52, no.2, pp.238-248, 2005.
[4] L. M. Heikkinen, M.Vauhkonen, T. Savolainen, and J. P. Kaipio, “Modelling of internal structures and electrodes in electrical process tomography” Meas. Sci. Technol., vol.12, pp.1012-1019, 2001.
[5] W.-L. Huang, EIT System Circuits Optimization and Simulation for Tissue Monitoring Application, Master Thesis, Institute of Biomedical Engineering, National Cheng Kung University, Taiwan, 2005.
[6] Ø. Isaksen, “A review of reconstruction techniques for capacitance tomography,” Meas. Sci. Technol, vol.7, pp.325-337, 1996.
[7] T. E. Kerner, D. B. Williams, K. S. Osterman, F. R. Reiss, A. Hartov. and K. Paulsen, “Electrical impedance image at multiple frequencies in phantoms,” Physiol. Meas., vol.21, pp. 67–77, 2000.
[8] K. Y. Kim, Y. B. Choi , B. S. Kim , M. C. Kim , J. H. Lee , J. W. Park , and Y. J. Lee, “Regularized modified Newton Raphson algorithm for electrical impedance tomography based on the exponentially weighted least square criterion ,” Proc. TENCON, vol.1, pp. 64-68, 2000.
[9] W. R. B. Lionheart, J. Kaipio, and C. N McLeod, “Generalized optimal current patterns and electrical safety in EIT,” Physiol. Meas., vol.22, pp.85–90, 2001.
[10]J. L. Mueller, D. Isaacson, and J. C. Newell, “Reconstruction of conductivity changes due to ventilation and perfusion from EIT data collected on a rectangular electrode array,” Phys. Med. Biol., vol.22, pp.97–106, 2001.
[11]M. Soleimani, G. L. Camille, and A. Adler, “Imaging of conductivity changes and electrode movement in EIT,” Physiol. Meas., vol. 27, pp.103–113, 2006..
[12]B. C. D. Simone, R. Sicillano, A. Pachi, C. Cametti, and F. De Luca, “Electrical impedance tomography via filtered-back projection of fan current distribution: A numerical simulation,” Bioelectromagnetics, vol.23, pp.516-521, 2002.
[13]M. Soleimani, “Electrical impedance tomography system: an open access circuit design,” BioMedical Engineering Online, vol.5, pp.28, 2006.
[14]H.-S. Tung, Comparisons of the Reconstruction Algorithms for the Electrical Impedance Imaging, Master Thesis, Institute of Biomedical Engineering, National Cheng Kung University, Taiwan, 1995.
[15]M. Vauhkone, W. R. B. Lionheart, L. M. Heikkinnen, and P. J. Vauhkonnen, “A MATLAB package for the EIDORS project to reconstruct two-dimensional EIT images,” Physiol. Meas., vol.22, pp.107–111, 2001.
[16]M. Wang, “Inverse solution for electrical impedance tomography based on conjugate gradients methods,” Meas. Sci. Technol., vol.13, pp.101-117, 2002.
[17]C. Wang, and H. X. Wang, “An image reconstruction algorithm based on generalized inverse for medical impedance tomography,” Proc Int. Conf. IEEE Machine Learning and Cybermetics, vol.4, pp.2152- 2157, 2003.
[18]F.-H. Wu, Electrical Impedance Image Reconstruction Using DSP, Master Thesis, Institute of Biomedical Engineering, National Cheng Kung University, Taiwan, 1998.
[19]C.-F. Wu, Electrical Impedance Tomography Design for Tissue Electrical Property Application, Master Thesis, Institute of Biomedical Engineering, National Cheng Kung University, Taiwan, 2004
[20]J. G. Webster, Electrical Impedance Tomography, USA: Adam Hilger, 1990.
[21]W. L. Zhao, and F. Dong, “Realization of image reconstruction algorithms for ERT based on single drive electrode method,” Proc Int. Conf. Machine Learning and Cybernetics, vol.9, pp.5341- 5345, 2005.
[22]TMS320C6713 DSK Technical Reference.
[23]TMS320C6713 DSK Floating-Point Digital Signal Processor SPRU 189.
[24]TMS320C6713 DSK Floating-Point Digital Signal Processor SPRS 186.
[25]TMS320C6713 DSK Floating-Point Digital Signal Processor User’s Manual.
[26]TMS320C6000 DSP Design Workshop