工作单位

中国科学技术大学生物医学工程学院

中国科学院微观磁共振重点实验室

研究方向

数据/模型驱动的智能与影像技术开发

应用于生物医学的数学物理模型开发

电磁计算、反演问题、人工/机器智能

无损电磁成像系统设计与应用开发

在研课题

生物医学电磁成像技术

正电子发射断层成像技术

模型驱动的医学图像重建方法

数据驱动的高分辨医学图像重建

电子邮箱

dong2016@ustc.edu.cn

dong.liu@outlook.com

主持的主要研项目

1.基于深度神经网络的电阻抗图像重建方法研究，基金委面上项目，62371433，2024.01-2027.12，主持

2.基于参数化多相水平集方法的电阻抗成像算法研究，基金委面上项目，61871356，2019.01-2022.12，结题，主持

2. 面向固态量子传感的自旋系综测量与调控装置，国家重大科研仪器研制项，51727808，2018-01至2022-12，723万元，结题，课题负责人

代表性研究论文

1.  J Wang, Y Wang, J Deng and D Liu. Unsupervised Coordinate-Based Neural Network for Electrical Impedance Tomography. IEEE Transactions on Computational Imaging, 9:1213-1225, 2023. 

2. D Liu, J Wang, Q Shan, D Smyl, J Deng and J F Du. DeepEIT: deep image prior enabled electrical impedance tomography. IEEE Transactions on Pattern Analysis and Machine Intelligence, 45(8):9627-9638, 2023. 

3.Q Shan, J Wang and D Liu. Deep Image Prior Based PET Reconstruction From Partial Data. IEEE Transactions on Radiation and Plasma Medical Sciences, 2023. DOI 10.1109/TRPMS.2023.3280674

4.Y Song, Y Wang and D Liu. A nonlinear weighted anisotropic total variation regularization for electrical impedance tomography. IEEE Transactions on   Instrumentation and Measurements, 71:4010713, 2022.

5.D Gu, J Deng, D Smyl, D Liu and J F Du. Supershape Augmented Reconstruction Method Based on Boolean Operations in Electrical Impedance Tomography, IEEE Transactions on Instrumentation and Measurement, 70: 4507111, 2021.

6.D Liu and J F Du. Shape and topology optimization in electrical impedance tomography via moving morphable components method. Structural and Multidisciplinary Optimization, 64:585-598, 2021.

7.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, 70: 4503711, 2021

8.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.

9.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.

10.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.

11.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.

12. 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.

13. 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.

14.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.

15.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.

16.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

17.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

18. 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

19.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

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

21.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

22. 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

23.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.

24. 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

25. 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

26.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.

27.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)

28.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.