Leslie (Lei) Ying
PhD
Specialty/Research Focus
Compressed sensing; magnetic resonance imaging; image reconstruction
Selected Publications
- Y. Wang, S. Jia, H. Zhang, D. Kim, H. Babcock, X Zhuang, L. Ying, “Blind sparse inpainting reveals cytoskeletal filaments with sub-Nyquist localizations,” Optica, vol. 4, no. 10, pp. 1277-1284, October 2017.
- U. Nakarmi, Y. Wang, J. Lyu, D. Liang, L. Ying, “A kernel-based low-rank (KLR) model for low-dimensional manifold recovery in highly accelerated dynamic MRI,” IEEE Transactions on Medical Imaging, Epub, July 2017, DOI: 10.1109/TMI.2017.2723871.
- S. Wang, S. Tan, Y. Gao, Q. Liu, L. Ying, T. Xiao, Y. Liu, H. Zheng, D. Liang, “Learning joint-sparse codes for calibration-free parallel MR imaging (LINDBERG),” IEEE Transactions on Medical Imaging, Epub, August 2017, DOI: 10.1109/TMI.2017.2746086.
- Y. Zhu, X. Peng, Y. Wu, E. Wu, L. Ying, X. Liu, H. Zheng, D. Liang, “Direct diffusion tensor estimation using model-based method with spatial and parametric constraints,” Medical Physics, vol. 44, no. 2, pp. 570-580, February 2017.
- Yang, Y. Wang, L. Ying, “Sparsity-constrained PET image reconstruction with learned dictionaries,” Physics in Medicine and Biology, vol. 61, no. 17, pp. 6347-6368, September 2016.
- X. Peng, L. Ying, Y. Liu, J. Yuan, X. Liu, D. Liang, “Accelerated exponential parameterization of T2 relaxation with model-driven low rank and sparsity priors (MORASA),” Magnetic Resonance in Medicine, vol. 76, no. 6, pp. 1865-1878, December 2016.
- H. Wan, Y. Zhou, L. Ying, J. Meng, L. Song, J. Xia, “Enabling high-speed wide-field dynamic imaging in multifocal photoacoustic computed microscopy: a simulation study,” Applied Optics, vol. 55, no. 14, pp. 3724-3729, May 2016.
- S. Wang, J. Liu, Q. Liu, L. Ying, X. Liu, H. Zheng, D. Liang, “Iterative feature refinement for accurate undersampled MR image reconstruction,” Physics in Medicine and Biology, vol. 61, no. 9, pp. 3291-3326, April 2016.
- Y. Zhou, P. Pandit, V. Pedoia, J. Rivoire, Y. Wang, D. Liang, X. Li, L. Ying, “Accelerating T1ρ cartilage imaging using compressed sensing with iterative locally adapted support detection and JSENSE,” Magnetic Resonance in Medicine, vol. 75, no. 4, pp. 1617-1629, April 2016.
- R.-R. Chen, D. Liang, Y. Chang, L. Ying, “Image reconstruction from phased-array data based on multichannel blind deconvolution,” Magnetic Resonance Imaging, vol. 33, no. 9, pp. 1106-1113, November 2015.
- U. Nakarmi, J. Lyu, K. Slavakis, L. Ying, “M-MRI: A manifold-based framework to highly accelerated dynamic magnetic resonance imaging,” IEEE International Symposium on Biomedical Imaging, pp. 19-22, Melbourne, Australia, April 2017.
- B. Yang, L. Ying, J. Tang, “Enhancing Bayesian PET image reconstruction using neural networks,” IEEE International Symposium on Biomedical Imaging, pp. 1181-1184, Melbourne, Australia, April 2017.
- H. Li, Y. Wang, D. Liang, L. Ying, “A novel hybrid total variation minimization Algorithm for Compressed Sensing,” Compressive Sensing VI: From Diverse Modalities to Big Data Analytics, Anaheim, CA, USA, April 2017
- S. Wang, Z. Su, L. Ying, S. Zhu, X. Peng, F. Liang, D. Feng, D. Liang, “Accelerating magnetic resonance imaging via deep learning,” IEEE International Symposium on Biomedical Imaging, pp. 514-517, Prague, Czech Republic, April 2016.
- U. Nakarmi, Y. Zhou, J. Lyu, K. Slavakis, L. Ying, “Accelerating dynamic magnetic resonance imaging by nonlinear sparse coding,” IEEE International Symposium on Biomedical Imaging, pp. 510-513, Prague, Czech Republic, April 2016.
- J. Lyu, U. Nakarmi, C. Zhang, L. Ying, “Highly accelerated cardiac cine parallel MRI using low rank matrix completion and partial separability model,” SPIE Commercial+Scientific Sensing and Imaging, 98570B-98570B-6, Baltimore, MD, USA April 2016.
- H. Wan, D. Wang, J. Meng, L. Song, L Ying, J Xia, “Optimization of the image reconstruction procedure in multi-focal photoacoustic computed tomography,” SPIE BiOS, 970840-970840-7, 2016
- Jingyuan Lyu, Yihang Zhou, Ukash Nakarmi, Chao Shi, and Leslie Ying, “KerNL: Parallel imaging reconstruction using Kernel-based NonLinear method,” International Society of Magnetic Resonance in Medicine Scientific Meeting (ISMRM), pp. 2130, Toronto, ON, Canada, May 2015.
- Jingyuan Lyu, Yihang Zhou, Ukash Nakarmi, and Leslie Ying, “Highly Accelerated Dynamic Imaging Reconstruction using Low Rank Matrix Completion and Partial Separability Model”, International Society of Magnetic Resonance in Medicine Scientific Meeting (ISMRM), pp.2128, Toronto, ON, Canada, May 2015.
- Ukash Nakarmi, Yanhua Wang, Jingyuan Lyu and Leslie Ying, "Accelerating Dynamic Imaging using Compressed Sensing with Self-learned Nonlinear Dictionary (NL-D)", The IEEE International Symposium on Biomedical Imaging (ISBI), Brooklyn, NY, USA, April 2015.