J Shanghai Jiaotong Univ Sci ›› 2022, Vol. 27 ›› Issue (2): 211-218.doi: 10.1007/s12204-021-2333-1
收稿日期:
2019-10-29
出版日期:
2022-03-28
发布日期:
2022-05-02
通讯作者:
MA Yixina,b* (马艺馨), y.ma@sjtu.edu.cn
ZHANG Mingzhua (张明珠), MA Yixina,b* (马艺馨), HUANG Ningninga (黄宁宁), GE Haoa (葛浩)
Received:
2019-10-29
Online:
2022-03-28
Published:
2022-05-02
中图分类号:
. [J]. J Shanghai Jiaotong Univ Sci, 2022, 27(2): 211-218.
ZHANG Mingzhu(张明珠), MA Yixin* (马艺馨), HUANG Ningning (黄宁宁), GE Hao (葛浩). Survey of EIT Image Reconstruction Algorithms[J]. J Shanghai Jiaotong Univ Sci, 2022, 27(2): 211-218.
[35] | HYV¨ONEN N, MUSTONEN L. Generalized linearization techniques in electrical impedance tomography [J].Numerische Mathematik, 2018, 140(1): 95-120. |
[1] | KUEN J, WOO E, SEO J. Multi-frequency timedifference complex conductivity imaging of canine and |
[36] | CHUNG E T, CHAN T F, TAI X C. Electrical impedance tomography using level set representation and total variational regularization [J]. Journal of Computational Physics, 2005, 205(1): 357-372. |
human lungs using the KHU Mark1 EIT system [J].Physiological Measurement, 2009, 30(6): S149-S164. | |
[37] | LIU D, SMYL D, DU J F. A parametric level set-based approach to difference imaging in electrical impedance tomography [J]. IEEE Transactions on Medical Imaging,2019, 38(1): 145-155. |
[2] | TAWIL D S, RYE D, VELONAKI M. Improved image reconstruction for an EIT-based sensitive skin with multiple internal electrodes [J]. IEEE Transactions on Robotics, 2011, 27(3): 425-435. |
[38] | LIU D, KHAMBAMPATI A K, DU J F. A parametric level set method for electrical impedance tomography [J]. IEEE Transactions on Medical Imaging, 2018,37(2): 451-460. |
[3] | YANG Y, JIA J, SMITH S, et al. A miniature electrical impedance tomography sensor and 3-D image reconstruction for cell imaging [J]. IEEE Sensors Journal,2017, 17(2): 514-523. |
[39] | LIU D, GU D, SMYL D, et al. B-spline-based sharp feature preserving shape reconstruction approach for electrical impedance tomography [J]. IEEE Transactions on Medical Imaging, 2019, 38(11): 2533-2544. |
[4] | PILLOW J J, FRERICHS I, STOCKS J. Lung function tests in neonates and infants with chronic lung disease: Global and regional ventilation inhomogeneity [J]. Pediatric Pulmonology, 2006, 41(2): 105-121. |
[40] | LIU D, DU J. A moving morphable components based shape reconstruction framework for electrical impedance tomography [J]. IEEE Transactions on Medical Imaging, 2019, 38(12): 2937-2948. |
[5] | HUANG N N, MA Y X, ZHANG M Z, et al. Finite element modeling of human thorax based on MRI images for EIT image reconstructiong [J]. Journal of Shanghai Jiao Tong University (Science), 2021, 26(1): 33-39. |
[41] | CHO K H, KIM S, LEE Y J. A fast EIT image reconstruction method for the two-phase flow visualization[J]. International Communications in Heat and Mass Transfer, 1999, 26(5): 637-646. |
[6] | CAI Z X, LIAN B, WANG X D, et al.Dielectric characterization of normal thyroid lesions [J]. Biomedical Engineering and Clinical Medicine, 2017, 21(1): 17-21 (in Chinese). |
[42] | RIBEIRO R R, FEITOSA A R S, DE SOUZA R E,et al. Reconstruction of electrical impedance tomography images using genetic algorithms and non-blind search [C]//2014 IEEE 11th International Symposium on Biomedical Imaging. Beijing, China: IEEE, 2014: 153-156. |
[7] | WANG H, HE Y, YAN Q, et al. Correlation between the dielectric properties and biological activities of human ex vivo hepatic tissue [J]. Physics in Medicine and Biology, 2015, 60(6): 2603-2617. |
[43] | RIBEIRO R R, FEITOSA A R S, DE SOUZA R E, et al. A modified differential evolution algorithm for the reconstruction of electrical impedance tomography images [C]//5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC). Salvador,Brazil: IEEE, 2014: 1-6. |
[8] | YANG B, XU C H, DAI M, et al. An electrical impedance tomography imaging method incorporated with inhomogeneously-distributed skull resistivity [J].China Medical Devices, 2015, 30(8): 1-4 (in Chinese). |
[44] | LIU S H, JIA J B, ZHANG Y D, et al. Image reconstruction in electrical impedance tomography based on structure-aware sparse Bayesian learning [J]. IEEE Transactions on Medical Imaging, 2018, 37(9): 2090-2102. |
[9] | REN S J, TAN C, DONG F. Two phase flow visualization in an annular tube by an Electrical Resistance Tomography [C]//2012 IEEE International Conference on Imaging Systems and Techniques Proceedings.Manchester, UK: IEEE, 2012: 488-492. |
[10] | REN S J, DONG F, TAN C. High-precision electrical resistance tomography with external and internal electrode arrays [C]//2011 IEEE International Instrumentation and Measurement Technology Conference.Hangzhou, China: IEEE, 2011: 1-6. |
[11] | ZHAO Z, FRERICHS I, PULLETZ S, et al. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation [J]. Physiological Measurement, 2014, 35(6): 1083-1093. |
[12] | OH T I, WI H, KIM D Y, et al. A fully parallel multifrequency EIT system with flexible electrode configuration:KHU Mark2 [J]. Physiological Measurement,2011, 32(7): 835-849. |
[13] | SHI X T, YOU F S, HUO X Y, et al. High quality data acquisition system for electrical impedance tomography [J]. Journal of Data Acquisition and Processing,2010, 25(2): 259-263 (in Chinese). |
[14] | WENG W L, DICKIN F J. Improved modified Newton-Raphson algorithm for electrical impedance tomography [J]. Electronics Letters, 1996, 32(3): 206-207. |
[15] | MURAI T, KAGAWA Y. Electrical impedance computed tomography based on a finite element model [J].IEEE Transactions on Biomedical Engineering, 1985,BME-32(3): 177-184. |
[16] | PIANA M, BERTERO M. Projected Landweber method and preconditioning [J]. Inverse Problems,1997, 13(2): 441-463. |
[17] | M?LLER M F. A scaled conjugate gradient algorithm for fast supervised learning [J]. Neural Networks, 1993,6(4): 525-533. |
[18] | VAUHKONEN M, VAD′ASZ D, KARJALAINEN P A,et al. Tikhonov regularization and prior information in electrical impedance tomography [J]. IEEE Transactions on Medical Imaging, 1998, 17(2): 285-293. |
[19] | KIM H C, KIM K Y, PARK J W, et al. Electrical impedance tomography reconstruction algorithm using extended Kalman filter [C]//2001 IEEE International Symposium on Industrial Electronics Proceedings. Pusan,Korea: IEEE, 2001: 1677-1681. |
[20] | MIAO L, MA Y, WANG J. ROI-based image reconstruction of electrical impedance tomography used to detect regional conductivity variation [J]. IEEE Transactions on Instrumentation and Measurement, 2014,63(12): 2903-2910. |
[21] | CHEN X Y, ZHANG J. Using threshold correction method to improve the image quality of EIT [J]. Chinese Journal of Biomedical Engineering, 2011, 30(4):481-486 (in Chinese). |
[22] | KNUDSEN K, LASSAS M, MUELLER J L, et al. Dbar method for electrical impedance tomography with discontinuous conductivities [J]. SIAM Journal on Applied Mathematics, 2007, 67(3): 893-913. |
[23] | BERETTA E, MICHELETTI S, PEROTTO S, et al.Reconstruction of a piecewise constant conductivity on a polygonal partition via shape optimization in EIT[J]. Journal of Computational Physics, 2018, 353: 264-280. |
[24] | CHEN X Y, SHI B, CHU M L, et al. Using neural network to improve the quality of EIT imaging [J].Journal of Tianjin University of Science & Technology,2016, 31(4): 74-78 (in Chinese). |
[25] | ZHANG K, LI M K, YANG F, et al. Application of multiplicative regularization for electrical impedance tomography [C]//2017 IEEE International Symposium on Antennas and Propagation & USNC/URSI National Radio Science Meeting. San Diego, CA, USA: IEEE, 2017: 27-28. |
[26] | WANG H X, TANG L, CAO Z. An image reconstruction algorithm based on total variation with adaptive mesh refinement for ECT [J]. Flow Measurement and Instrumentation, 2007, 18(5/6): 262-267. |
[27] | GONG B, SCHULLCKE B, KRUEGER-ZIOLEK S, et al. Higher order total variation regularization for EIT reconstruction [J]. Medical & Biological Engineering & Computing, 2018, 56(8): 1367-1378. |
[28] | YANG Y, JIA J. An image reconstruction algorithm for electrical impedance tomography using adaptive group sparsity constraint [J]. IEEE Transactions on Instrumentation and Measurement, 2017, 66(9): 2295-2305. |
[29] | YANG Y, WU H, JIA J. Image reconstruction for electrical impedance tomography using enhanced adaptive group sparsity with total variation [J]. IEEE Sensors Journal, 2017, 17(17): 5589-5598. |
[30] | MARTINS T D C, TSUZUKI M D S G, CAMARGO E D L B D, et al. Interval Simulated Annealing applied to Electrical Impedance Tomography image reconstruction with fast objective function evaluation [J]. Computers & Mathematics with Applications, 2016, 72(5):1230-1243. |
[31] | KNUDSEN K,MUELLER J, SILTANEN S. Numerical solution method for the dbar-equation in the plane [J].Journal of Computational Physics, 2004, 198(2): 500-517. |
[32] | HAMILTON S J, HAUPTMANN A. Deep D-bar:Real-time electrical impedance tomography imaging with deep neural networks [J]. IEEE Transactions on Medical Imaging, 2018, 37(10): 2367-2377. |
[33] | ALESSANDRINI G. Stable determination of conductivity by boundary measurements [J]. Applicable Analysis,1988, 27(1/2/3): 153-172. |
[34] | HECK H. Stability estimates for the inverse conductivity problem for less regular conductivities [J]. Communications in Partial Differential Equations, 2009,34(2): 107-118. |
[35] | HYV¨ONEN N, MUSTONEN L. Generalized linearization techniques in electrical impedance tomography [J].Numerische Mathematik, 2018, 140(1): 95-120. |
[36] | CHUNG E T, CHAN T F, TAI X C. Electrical impedance tomography using level set representation and total variational regularization [J]. Journal of Computational Physics, 2005, 205(1): 357-372. |
[37] | LIU D, SMYL D, DU J F. A parametric level set-based approach to difference imaging in electrical impedance tomography [J]. IEEE Transactions on Medical Imaging,2019, 38(1): 145-155. |
[38] | LIU D, KHAMBAMPATI A K, DU J F. A parametric level set method for electrical impedance tomography [J]. IEEE Transactions on Medical Imaging, 2018,37(2): 451-460. |
[39] | LIU D, GU D, SMYL D, et al. B-spline-based sharp feature preserving shape reconstruction approach for electrical impedance tomography [J]. IEEE Transactions on Medical Imaging, 2019, 38(11): 2533-2544. |
[40] | LIU D, DU J. A moving morphable components based shape reconstruction framework for electrical impedance tomography [J]. IEEE Transactions on Medical Imaging, 2019, 38(12): 2937-2948. |
[41] | CHO K H, KIM S, LEE Y J. A fast EIT image reconstruction method for the two-phase flow visualization[J]. International Communications in Heat and Mass Transfer, 1999, 26(5): 637-646. |
[42] | RIBEIRO R R, FEITOSA A R S, DE SOUZA R E,et al. Reconstruction of electrical impedance tomography images using genetic algorithms and non-blind search [C]//2014 IEEE 11th International Symposium on Biomedical Imaging. Beijing, China: IEEE, 2014: 153-156. |
[43] | RIBEIRO R R, FEITOSA A R S, DE SOUZA R E, et al. A modified differential evolution algorithm for the reconstruction of electrical impedance tomography images [C]//5th ISSNIP-IEEE Biosignals and Biorobotics Conference (2014): Biosignals and Robotics for Better and Safer Living (BRC). Salvador,Brazil: IEEE, 2014: 1-6. |
[44] | LIU S H, JIA J B, ZHANG Y D, et al. Image reconstruction in electrical impedance tomography based on structure-aware sparse Bayesian learning [J]. IEEE Transactions on Medical Imaging, 2018, 37(9): 2090-2102. |
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