Prof. Dong Liu
.
Author:臧晶晶  Release time:2020-05-27   Access times:749

Name: 

Dong Liu, Research Professor

Address:

Room 517, East Block, Science and Technology Building, West Campus, USTC, No.443, Huangshan Road, Hefei, Anhui, 230027, China

Tel:

+86 551 6360 0469

E-mail:

Dong.liu(a)outlook.com

 EDUCATION AND RESEARCH EXPERIENCE

2001.9-2005.7

Shanghai Jiao Tong University, China, B.S., Applied Physics

2005.8-2009.8

China Academy of Engineering Physics, Research assistant

2009.9-2011.7

2011.9-2015.12

2015.12-2016.2

Jeju National University, Korea, M.Sc. Electronic Engineering

University of Eastern Finland, Finland, Ph.D., Applied Physics

University of Eastern Finland, Finland, Project Researcher

2016.3-2020.4


2020.5-present


University of Science and technology of China, Department of

Modern Physics, Research Fellow

University of Science and technology of China, Department of Modern Physics, Research Professor

 

RESEARCH INTERESTS

  • Finite element modeling

  • Computational inverse problems

  • Electrical Impedance Tomography

  • Mathematical modeling and computational physics

 

CURRENT RESEARCH PROJECTS

1.

A parametric multiphase level set based reconstruction algorithm for electrical impedance tomography, NSFC, Grant No 61871356

 

REPRESENTATIVE PUBLICATIONS

  1. D Gu, D Liu, D Smyl, J Deng and J F Du. Supershape recovery from electrical impedance tomography data, IEEE Transactions on Instrumentation and Measurement, in press, 10.1109/TIM.2021.3064802

  2. D Liu, D Gu, D Syml, A Khambampati, J Deng and J F Du. Shape-driven EIT reconstruction using Fourier representations. IEEE Transactions on Medical Imaging, 40(2), 481-490, 2021.

  3. D Liu, D Syml, D Gu and J F Du. Shape-driven difference electrical impedance tomography. IEEE Transactions on Medical Imaging, 39(12), 3801-3812, 2020.

  4. D Liu, D Gu, D Syml, J Deng and J F Du. Multiphase conductivity imaging with Electrical Impedance Tomography and B-spline level set method. IEEE Transactions on Instrumentation and Measurement, 69(12), 9634-9644, 2020.

  5. D Liu, D Gu, D Syml, J Deng and J F Du. Shape reconstruction using Boolean operations in electrical impedance tomography. IEEE Transactions on Medical Imaging, 39(9), 2954-2964, 2020.

  6. D Syml and D Liu, Optimizing Electrode Positions in 2-D Electrical Impedance Tomography Using Deep Learning. IEEE Transactions on Instrumentation and Measurement, 69(9), 6030-6044, 2020.

  7. D Liu, D Gu, D Syml, J Deng and J F Du. B-Spline Level Set Method for Shape Reconstruction in Electrical Impedance Tomography. IEEE Transactions on Medical Imaging, 39(6), 1917-1929, 2020.

  8. D Liu, D Syml and J F Du. Nonstationary shape estimation in electrical impedance tomography using a parametric level-set-based extended Kalman filter approach. IEEE Transactions on Instrumentation and Measurement, 69(5), 1894-1907, 2020.

  9. Z Li, J Zhang, D Liu and J F Du. CT Image-Guided Electrical Impedance Tomography for Medical Imaging. IEEE Transactions on Medical Imaging, 39(6), 1822-1832, 2020.

  10. D Smyl, S Bossuyt, W Ahmad, A Vavilov and D Liu. An overview of 38 least squares-based frameworks for structural damage tomography. Structural Health Monitoring, 19(1), 215-239, 2020

  11. D Liu and J F Du. A moving morphable components based shape reconstruction framework for electrical impedance tomography. IEEE Transactions on Medical Imaging, 38(12), 2937-2948, 2019

  12. D Liu, D Gu, D Syml, J Deng and J F Du. B-spline based sharp feature preserving shape reconstruction approach for electrical impedance tomography. IEEE Transactions on Medical Imaging, 38(11), 2533-2544, 2019

  13. D Liu, D Syml and J F Du. A Parametric Level Set based Approach to Difference Imaging in Electrical Impedance Tomography. IEEE Transactions on Medical Imaging, 38(1), 145-155,2019

  14. D Smyl and D Liu. Less is often more: Applied inverse problems using hp-forward models. Journal of Computational Physics, 399(108949), 2019

  15. S Ren, K Sun, D Liu and F Dong. A Statistical Shape Constrained Reconstruction Framework for Electrical Impedance Tomography. IEEE Transactions on Medical Imaging, 38(10), 2400-2410, 2019

  16. Z Wei, D Liu and X Chen. Dominant-Current Deep Learning Scheme for Electrical Impedance Tomography. IEEE Transactions on Biomedical Engineering, 66(9), 2546-2555, 2019

  17. D Liu, Y X Zhao, A Khambampati, A Seppanen and J F Du. A parametric level set method for imaging multi-phase conductivity using electrical impedance tomography. IEEE Transactions on Computational Imaging, 4(4), 552-561, 2018.

  18. D Liu, A K Khambampati and J F Du. A Parametric Level Set Method for Electrical Impedance Tomography. IEEE Transactions on Medical Imaging, 37(2), 451-460, 2018

  19. D Liu, E Kankare, A-M Laukkanen and P Alku. Comparison of parametrization methods of electroglottographic and inverse filtered acoustic speech pressure signals in distinguishing between phonation types. Biomedical Signal Processing and Control, 36, 183-193, 2017

  20. D Liu , V Kolehmainen, S Siltanen, A-M Laukkanen and A Seppänen. Non-linear difference imaging approach to three-dimensional electrical impedance tomography in the presence of geometric modeling error. IEEE Transactions on Biomedical Engineering, 63(9):1956-1965, 2016.

  21. D Liu, V Kolehmainen, S Siltanen and A Seppänen, A non-linear approach to difference imaging in EIT; assessment of the robustness in the presence of modelling errors. Inverse Problems 31. 035012, 2015. (highlight article)

  22. D Liu, V Kolehmainen, S Siltanen, A-M Laukkanen and A Seppänen. Estimation of conductivity changes in a region of interest with electrical impedance tomography. Inverse Problems and Imaging 9(1). 211-229. 2015.