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  冯原

  
  

  冯原博士分别于2006年和2008年在哈尔滨工业大学获得学士和硕士学位，2012年在美国圣路易斯华盛顿大学获得机械工程博士学位。2013年和2014年分别在圣路易斯华盛顿大学医学院和德州大学奥斯汀分校从事博士后研究；2014年底就职苏州大学，2018年加入上海交通大学生物医学工程学院；建立了电磁驱动弹性成像系统并在临床应用推广，开发了实时磁共振介入成像方法并应用于脑组织介入手术机器人，建立了基于生物力学开展脑科学和脑疾病的理论和方法，已发表期刊论文46篇，授权发明专利13项，承担国自然面上项目2项，优青项目1项，以及重点研发计划子课题1项，主要研究方向是脑生物力学和磁共振成像。

  
  

  
  

教授 上海交通大学生物医学工程学院 2024至今

副教授 上海交通大学生物医学工程学院 2018-2024

脑生物力学，磁共振弹性成像，磁共振介入成像

实验室网址：https://faculty.sjtu.edu.cn/fengyuan/zh_CN/index.htm；https://github.com/aaronfeng369

1.      冯原, 何钊, 孙青芳, 孙伯民, 严福华, 杨广中. 磁共振介入成像及其临床应用, 《诊断学理论与实践》,  Advances in interventional magnetic resonance imaging and its clinical applications, J Diagn Concepts Pract, 2024, 23(2):108-113.

2.      Feng, Y.^*, Qiu, S., Yan, F., Yang, G-Z., (2024) Magnetic Resonance Elastography and its application in brain diseases, Chinese J Magn Reson, 41(2):209-223. 冯原，邱苏豪，严福华，杨广中，磁共振弹性成像及其在脑疾病中的应用，《波谱学杂志》, 2024, 41(2):209-223.

3.      Bao, Y., Qiu, S., Li, Z., Yang, G., Feng, Y., Yue, Q. (2024). Preoperative assessment of meningioma consistency using a combination of magnetic resonance elastography and diffusion tensor imaging. American Journal of Neuroradiology, ajnr.A8385.

4.      Suhao Qiu, Zhao He, Runke Wang, Ruokun Li, Wei Jin, Liang Chen, Jun Liu, Fuhua Yan, GuangZhong Yang, and Yuan Feng* (2024). Indirect Shear Wave Excitation for Brain Magnetic Resonance Elastography with Minimal Cerebral Blood Flow Alteration, IEEE Transactions on Biomedical Engineering.

5.      Wang, R. ^#, Wang, Y. ^#, Qiu, S., Ma, S., Yan, F., Yang, G.-Z.*, Li, R.*, Feng, Y.* (2024), A Comparative Study of Three Systems for Liver Magnetic Resonance Elastography. J Magn Reson Imaging. 

6.      Xu, C.-X., Kong, L., Jiang, H., Jiang, Y., Sun, Y.-H., Bian, L.-G., Feng, Y., & Sun, Q.-F. (2024). Analysis of brain structural covariance network in Cushing disease. Heliyon, 10(7), e28957.

7.      He, Z., Y.-N. Zhu, Y. Chen, Y. Chen, Y. He, Y. Sun, T. Wang, C. Zhang, B. Sun, F. Yan, X. Zhang, Q.-F. Sun, G.-Z. Yang and Y. Feng (2023). A deep unrolled neural network for real-time MRI-guided brain intervention. Nature Communications 14(1): 8257.

8.      Lin, H., Qiu, S., Yang, Y., Yang, C., Shen, Z., Chen, Y., Zhang, Z., Feng, Y.*, & Yan, F.* (2023). Three-dimensional magnetic resonance elastography combining proton-density fat fraction precisely identifies metabolic dysfunction-associated steatohepatitis with significant fibrosis. Magnetic Resonance Imaging, 104, 1-8.

9.      Huang, S., Lou, C., Zhou, Y., He, Z., Jin, X., Feng, Y., Gao, A., & Yang, G.-Z.* (2023). MRI-guided robot intervention—current state-of-the-art and new challenges. Med-X, 1(1), 4.

10.  Feng, Y.*, Murphy, M. C., Hojo, E., Li, F., & Roberts, N. (2023). Magnetic Resonance Elastography in the Study of Neurodegenerative Diseases. Journal of magnetic resonance imaging.

11.  Ma, S., Wang, R., Qiu, S., Li, R., Yue, Q., Sun, Q., Chen, L., Yan, F., Yang, G. Z., & Feng, Y.* (2023). MR Elastography With Optimization-Based Phase Unwrapping and Traveling Wave Expansion-Based Neural Network (TWENN). IEEE Transactions on Medical Imaging, 42(9), 2631-2642.

12.  Kong, L., Qiu, S., Chen, Y., He, Z., Huang, P., He, Q., Zhang, R., Feng, X-Q., Deng, L., Li, Y., Yan, F., Yang, G-Z., Feng, Y.*, Assessment of vibration modulated regional cerebral blood flow with MRI, NeuroImage, 2023, 119934.

13.  Chen, Y., Li, R., Yang, Y., Ma, D., Zhou, J., Wang, C., Kong, L., Chen, Y., Yan, F., & Feng, Y.* (2022). Correlation analysis of structural and biomechanical properties of hepatocellular carcinoma tissue. Journal of Biomechanics, 141, 111227.

14.  Feng, Y.*, Qiu, S. H., Chen, Y., Wang, R. K., He, Z., Kong, L. H., Chen, Y., & Ma, S. Y. (2022). Viscoelastic Characterization of Soft Tissue-Mimicking Gelatin Phantoms using Indentation and Magnetic Resonance Elastography. Jove-Journal of Visualized Experiments(183).

15.  Feng, Y.*, Chen, Y., Yao, Y., Li, X., Zhang, A., & Genin, G. M. (2022). The brain as a structure: A model of how fluid–structure interactions stiffen brain tissue after injury. Engineering Structures, 256, 113960.

16.  He, Z., Zhu, Y. N., Qiu, S., Wang, T., Zhang, C., Sun, B., Zhang, X.*, & Feng, Y.* (2022). Low-Rank and Framelet Based Sparsity Decomposition for Interventional MRI Reconstruction. IEEE Transactions on Biomedical Engineering, 69(7), 2294-2304.

17.  Wang, R., Chen, Y., Li, R., Qiu, S., Zhang, Z., Yan, F., & Feng, Y.* (2022). Fast magnetic resonance elastography with multiphase radial encoding and harmonic motion sparsity based reconstruction. Phys Med Biol, 67(2), 25007.

18.  Qiu, S., He, Z., Wang, R., Li, R., Zhang, A., Yan, F., & Feng, Y. *(2021). An electromagnetic actuator for brain magnetic resonance elastography with high frequency accuracy. NMR in Biomedicine, e4592, 1–17. (cover image paper)

19.  Chen, Y., Qiu, S., He, Z., Yan, F., Li, R., & Feng, Y. *(2021). Comparative analysis of indentation and magnetic resonance elastography for measuring viscoelastic properties. Acta Mechanica Sinica, 37(3), 527–536.

20.  Lai, C., Chen, Y., Wang, T., Liu, J., Wang, Q., Du, Y., & Feng, Y. *(2020). A machine learning approach for magnetic resonance image–based mouse brain modeling and fast computation in controlled cortical impact. Medical & Biological Engineering & Computing, 58(11), 2835-2844.

21.  Chen, Y., Qiu, S., Wang, C., Li, X., Tang, Y., & Feng, Y.* (2020). Measurement of viscoelastic properties of injured mouse brain after controlled cortical impact. Biophysics Reports, 6(4), 137-145.

22.  Zufiria, B., Qiu, S., Yan, K., Zhao, R., Wang, R., She, H., Zhang, C., Sun, B., Herman, P., Du, Y.,Feng, Y.* (2019). A feature-based convolutional neural network for reconstruction of interventional MRI. NMR in Biomedicine, e4231.

23.  Qiu, S., Jiang, W., Alam, M. S., Chen, S., Lai, C., Wang, T., Li, X., Liu, J., Gao, M., Tang, Y., Li, X., Zeng, J.*, & Feng, Y.* (2020). Viscoelastic characterization of injured brain tissue after controlled cortical impact (CCI) using a mouse model. Journal of Neuroscience Methods, 330, 108463.

24.  Li, Y.^#, Lai, C. ^#, Zhang, C., Singer, A., Qiu, S., Sun, B., Sacks, M. S., Feng, Y.* (2019). Magnetic Resonance Image-Based Modeling for Neurosurgical Interventions. Molecular & Cellular Biomechanics, 16(4), 245–251. https://doi.org/10.32604/mcb.2019.07441

25.  Ma, S., Zhu, M., Xia, X., Guo, L., Genin, G. M., Sacks, M. S., Gao, M., Mutic, S., Hu, Y., Hu, C.-h., & Feng, Y.* (2019). A preliminary study of the local biomechanical environment of liver tumors in vivo. Med Phys, 46(4), 1728-1739.

26.  Pei, W., Chen, J., Wang, C., Qiu, S., Zeng, J., Gao, M., Zhou, B., Li, D., Sacks, M. S., Han, L., Shan, H., Hu, W.*, Feng, Y.*, & Zhou, G.* (2019). Regional biomechanical imaging of liver cancer cells. J Cancer, 10(19), 4481-4487.

27.  Chen, Jiayao^#, Bin Zhou^#, Suhao Qiu^#, Shengyuan Ma, Chung-Hao Lee, Ankush Aggarwal, Jianfeng Zeng, Mingyuan Gao, Yuan Feng*, Dan Li* and Hong Shan*. "Evaluation of the Laser-Induced Thermotherapy Treatment Effect of Breast Cancer Based on Tissue Viscoelastic Properties." Journal of Engineering and Science in Medical Diagnostics and Therapy 1, no. 4 (2018): 041009-041009-9.

28.  Feng Y^*#, Zhu M^#, Qiu S, Shen P, Ma S, Zhao X, et al. A multi-purpose electromagnetic actuator for magnetic resonance elastography. Magnetic Resonance Imaging. 2018;51:29-34. IF2.38

29.  Qiu, Suhao, Xuefeng Zhao, Jiayao Chen, Jianfeng Zeng, Shuangqing Chen, Lei Chen, You Meng, Biao Liu, Hong Shan, Mingyuan Gao and Yuan Feng*. "Characterizing Viscoelastic Properties of Breast Cancer Tissue in a Mouse Model Using Indentation." Journal of Biomechanics 69, (2018): 81-89.

30.  S. Potter, J. Graves, B. Drach, T. Leahy, C. Hammel, Y. Feng, A. Baker and M. S. Sacks. A Novel Small-Specimen Planar Biaxial Testing System With Full In-Plane Deformation Control. Journal of biomechanical engineering 140: 051001-051001-051018, 2018.

31.  L. Chen, J. Chen, S. Qiu, L. Wen, Y. Wu, Y. Hou, Y. Wang, J. Zeng, Y. Feng, Z. Li, H. Shan and M. Gao. Biodegradable Nanoagents with Short Biological Half-Life for SPECT/PAI/MRI Multimodality Imaging and PTT Therapy of Tumors. Small 2017.

32.  Y. Feng*, F. Dong, X. Xia, C. H. Hu, Q. Fan, Y. Hu, M. Gao and S. Mutic. An adaptive Fuzzy C-means method utilizing neighboring information for breast tumor segmentation in ultrasound images. Med Phys 44: 3752-3760, 2017. doi: 10.1002/mp.12350.

33.  Y. Feng*^#, Y. Gao^#, T. Wang, L. Tao, S. Qiu and X. Zhao. A longitudinal study of the mechanical properties of injured brain tissue in a mouse model. Journal of the Mechanical Behavior of Biomedical Materials 71: 407-415, 2017. doi: 10.1016/j.jmbbm.2017.04.008.

34.  Y. Feng*^#, C.-H. Lee^#, L. Sun, S. Ji and X. Zhao. Characterizing white matter tissue in large strain via asymmetric indentation and inverse finite element modeling. Journal of the Mechanical Behavior of Biomedical Materials 65: 490-501, 2017. http://doi.org/10.1016/j.jbiomech.2017.03.025.

35.  W. Zheng^#, H. Yang^#, G. Xuan, L. Dai, Y. Hu, S. Hu, S. Zhong, Z. Li*, M. Gao, S. Wang and Y. Feng*. Longitudinal Study of the Effects of Environmental pH on the Mechanical Properties of Aspergillus niger. ACS Biomaterials Science & Engineering 3: 2974-2979, 2017.

36.  Y. Feng*, S. Qiu, X. Xia, S. Ji and C.-H. Lee. A computational study of invariant I5 in a nearly incompressible transversely isotropic model for white matter. Journal of Biomechanics 57: 146-151, 2017.

37.  Y. Feng, E. H. Clayton, R. J. Okamoto, J. Engelbach, P. V. Bayly and J. R. Garbow*. A longitudinal magnetic resonance elastography study of murine brain tumors following radiation therapy. Physics in Medicine and Biology 61: 6121, 2016. doi:http://dx.doi.org/10.1088/0031-9155/61/16/6121.

38.  Y. Feng*, R. J. Okamoto, G. M. Genin and P. V. Bayly. On the accuracy and fitting of transversely isotropic material models. Journal of the Mechanical Behavior of Biomedical Materials 61: 554-566, 2016. doi: 10.1016/j.jmbbm.2016.04.024.

39.  Y. Feng*, H. Guo, H. Zhang, C. Li, L. Sun, S. Mutic, S. Ji and Y. Hu. A modified fuzzy c-means method for segmenting MR images using non-local information. Technol Health Care 24: S785-793, 2016.

40.  Y. Feng, I. Kawrakow, J. Olsen, P. J. Parikh, C. Noel, O. Wooten, D. S. Du, S. Mutic and Y. L. Hu*. A comparative study of automatic image segmentation algorithms for target tracking in MR-IGRT. Journal of Applied Clinical Medical Physics 17: 441-460, 2016. doi:10.1120/jacmp.v17i2.5820. IF1.34

41.  W. Zhang, Y. Feng, C.-H. Lee, K. L. Billiar and M. S. Sacks*. A Generalized Method for the Analysis of Planar Biaxial Mechanical Data Using Tethered Testing Configurations. Journal of biomechanical engineering 137: 064501-064501, 2015.

42.  Y. Feng, R. J. Okamoto, R. Namani, G. M. Genin and P. V. Bayly*. Measurements of mechanical anisotropy in brain tissue and implications for transversely isotropic material models of white matter. Journal of the Mechanical Behavior of Biomedical Materials 23: 117-132, 2013. doi:10.1016/j.jmbbm.2013.04.007.

43.  Y. Feng, E. H. Clayton, Y. Chang, R. J. Okamoto and P. V. Bayly*. Viscoelastic properties of the ferret brain measured in vivo at multiple frequencies by magnetic resonance elastography. Journal of Biomechanics 46: 863-870, 2013. doi: 10.1016/j.jbiomech.2012.12.024.

44.  R. Namani, Y. Feng, R. J. Okamoto, N. Jesuraj, S. E. Sakiyama-Elbert, G. M. Genin and P. V. Bayly*. Elastic characterization of transversely isotropic soft materials by dynamic shear and asymmetric indentation. J Biomech Eng 134: 061004, 2012. doi: 10.1115/1.4006848. IF2.06

45.  T. M. Abney, Y. Feng, R. Pless, R. J. Okamoto, G. M. Genin and P. V. Bayly*. Principal Component Analysis of Dynamic Relative Displacement Fields Estimated from MR Images. PLoS One 6: e22063, 2011.

[1]生物力学,秋学期,2020-2021

[2]生物力学II,秋学期,1-16周,星期五第7-9节(东上院/东上院211) ,1-16周,星期五第7-9节(东上院/东上院211) ,2019-2020

[3]磁共振快速成像理论与应用,春学期,1-16周,星期二第7-8节(工程馆/工程馆210) ,1-16周,星期二第7-8节(工程馆/工程馆210) ,2019-2020

[4]生物力学,秋学期,2019-2020

[5]生物力学,秋学期,2018-2019

[6]生物力学II,秋学期,1-16周,星期五第3-4节(上课地点未定) ,1-16周,星期五第3-4节(上课地点未定) ,2018-2019

1. 生物软组织力学特性测试仪及生物软组织的力学测试方法，发明专利，专利号201510701187.2，已授权（2017.9.28）
2. 生物软组织微观力学特性测试仪，发明专利，专利号201610890055.3，已授权（2018.1.11）
3. 生物软组织的力学特性测试仪，发明专利，专利号201510412004.5，已授权（2018.7.13）

4. 用于手术规划的肺部组织三维重建与可视化装置，发明专利，专利号201810564357.0，已授权（2019.12.4）

5. 头部磁共振弹性成像驱动装置，实用新型专利，专利号：ZL201720516657.2，已授权（2018.1.5）
6. 生物软组织挤压测试仪操作软件，计算机软件著作权，登记号2015SR251006，已授权（2015.8.12）
7. 一种用于磁共振测试的软组织模拟器，实用新型专利，专利号：201720381046.1，已授权（2017.10.10）
8. 一种用于动物和体外样本磁共振弹性成像的驱动装置，实用新型专利，专利号：20172013065.3，已授权（2018.02.01）
9.  胸腹磁共振弹性成像驱动装置，实用新型专利，专利号：201720288856.2，已授权（2018.03.26）
10. A Mechanical Property Tester of Biological Soft Tissue，PCT/CN2015/084451，US 15/106,769，已授权
11. Mechanical property tester and testing method of biological soft tissue, PCT/CN2015/093628，US 15/308,168. 已授权（2018.04.11）
12. Medical Image Segmentation Method and Apparatus, US 15/387,886, 已授权（2018.09.05）