Invited Talks (26)
1. Implementation of Katsevich-type algorithms for helical cone-beam CT; July 22, 2004, Xi’an, Shaanxi, China.
2. Development of spiral cone-beam methods; May 16, 2006, Minneapolis, MN, US
3. Skew cone-beam lambda tomography; Aug 15-17, 2006, San Diego, CA, US
4. Utah Center for Advanced Imaging Research Seminar, July 23, 2008, Salt Lake City, UT, US
5. Development of interior tomography: theory and algorithms, Aug. 10-14, 2008, San Diego, CA, USA
6. Chongqing Thee Gorges University Seminar, Sep. 24, 2009, Wanzhou, Chongqing, China
7. Chongqing University Seminar, Sep. 28, 2009, Chongqing, P.R. China.
8. Interior tomography, GE Global Research Center, Feb. 17, 2010, Albany, NY. (with Ge Wang)
9. Recent progress of local reconstruction, Aug. 2-6, 2010, San Diego, CA, USA
10. General cone-beam reconstruction and interior tomography in x-ray CT, Georgia Southern University, Nov. 17, 2010, Statesboro, GA.
11. Dictionary learning based low-dose CT, Michigan State University, Aug 26-28, 2011.
12. Applications of Compressive Sensing in Computed Tomography, Emory University, Oct. 26, 2012, Atlanta, GA.
13. Spectrography for 3D analysis from a single spectral view, Aug. 24-27, 2013, San Diego, CA, USA.
14. Compressive Sensing in Computed Tomography; UMass Medical School, Dec. 19, 2014.
15. Compressive Sensing in Computed Tomography; Southeast University, China, Jan. 11, 2016.
16. Compressive Sensing in Computed Tomography; Xi’an University, China, Jan. 12, 2016.
17, Compressive Sensing in Spectral Computed Tomography, Capital Normal University, June 9, 2017.
18, Compressive Sensing in Spectral Computed Tomography, Shandong University, June 10, 2017.
19. Deep learning for metal artifact reduction, Rensselaer Polytechnic Institute, November 19, 2017.
20. Deep learning for metal artifact reduction, Medtronic Inc, June 19, 2018.
21. Dictionary learning based material decomposition
for spectral CT, Deep Reconstruction Workshop, GE Global Research, Jan.
15-16, 2020.
22. Ted-Net for low-dose CT denoising, 3rd
Deep Reconstruction Workshop, MGH, Nov. 14, 2021
23. Deep learning in tomographic imaging, Webinar, Xidian
University, China, Jan. 6, 2022.
24. Metal artifact reduction in CT, guest lecture,
WUSTL, St. Louis, Jan. 31, 2022.
25. CTformer: Convolution-free Transformer for
Low-dose CT Denoising. Shaanxi Biomedical Enginering Society Workshop,
online, Sep. 14, 2022.
26. Theoretical Analysis of ACID, 4th Deep Reconstruction
Workshop, Yale University, March 24-25, 2023Ted-Net for low-dose CT denoising, 3rd Deep Reconstruction Workshop, MGH, Nov. 14, 2021.