## Journal Publications

- J. He, Q. Liu, A. Christodoulou, C. Ma,
**F. Lam**, Z.-P. Liang.

Accelerated high-dimensional MR imaging with sparse sampling using low-rank tensors.

IEEE Transaction on Medical Imaging, vol. 35, pp. 2119-2129, 2016. **F. Lam**, D. Liu, Z. Song, N. Schuff and Z.-P. Liang.

A fast algorithm for rank and edge constrained denoising of magnitude diffusion-weighted images.

Magnetic Resonance in Medicine, 75:433-440, 2016.- B. Zhao, W. Lu, T. K. Hitchens,
**F. Lam**, C. Ho, and Z.-P. Liang.

Accelerated MR parameter mapping with low-rank and sparsity constraints.

Magnetic Resonance in Medicine, 74:489–498, 2015. **F. Lam**, S. D. Babacan, J. P. Haldar, M. W. Weiner, N. Schuff, and Z.-P. Liang.

Denoising diffusion-weighted magnitude MR images using rank and edge constraints.

Magnetic Resonance in Medicine, 71:1272-1284, 2014.- B. Zhao,
**F. Lam**and Z.-P. Liang.

Model-based MR parameter mapping with sparsity constraints: Parameter estimation and performance bounds.

IEEE Transactions on Medical Imaging, 33:1832-1844, 2014. - X. Qu, Y. Hou,
**F. Lam**, D. Guo, J. Zhong, and Z. Chen.

Magnetic resonance image reconstruction from undersampled measurements using a patch-based nonlocal operator.

Medical Image Analysis, 18:843-856, 2014. - J. Gai, N. Obeid, J. L. Holtrop, X.-L. Wu,
**F. Lam**, M. Fu, J. P. Haldar, W.-M. Hwu, Z.-P. Liang, and B. P. Sutton.

More IMPATIENT: A gridding-accelerated Toeplitz-based strategy for non-Cartesian high-resolution 3D MRI on GPUs.

Journal of Parallel and Distributed Computing, 73:686-697, 2013. - H. Du and
**F. Lam**.

Compressed sensing MR image reconstruction using a motion compensated reference.

Magnetic Resonance Imaging, 30:954-963, 2012.

## In Conference Proceedings

**F. Lam**, B. Zhao, and Z.-P. Liang. Joint estimation of spherical harmonic coefficients from magnitude diffusion-weighted images with sparsity constraints.*IEEE International Symposium on Biomedical Imaging*, New York, pp. 947-950, 2015.- B. Zhao,
**F. Lam**, B. Bilgicy, H. Yey, and K. Setsompop. Maximum likelihood reconstruction for magnetic resonance fingerprinting. IEEE International Symposium on Biomedical Imaging, New York, pp. 905-909, 2015. **F. Lam**, B. Zhao, Y. Liu, Z.-P. Liang, M. Weiner, and N. Schuff. Accelerated fMRI using low-rank model and sparsity constraints. International Society for Magnetic Resonance in Medicine, Salt Lake City, p. 2417, 2013.**F. Lam**, B. Zhao, M. Weiner, N. Schuff, and Z.-P. Liang. Denoising image sequences: Algorithm and application to quantitative MR imaging. International Society for Magnetic Resonance in Medicine, Salt Lake City, p. 2471, 2013.**F. Lam**, C. Ma, and Z.-P. Liang. Performance analysis of denoising with low-rank and sparsity constraints. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, San Francisco, pp. 1211-1214, 2013.- S. D. Babacan,
**F. Lam**, X. Peng, M. N. Do, and Z.-P. Liang. Interventional MRI with sparse sampling using union-of-subspaces. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 314-317, 2012. **F. Lam**, S. D. Babacan, N. Schuff, and Z.-P. Liang. Denoising diffusion-weighted MR Images using low rank structure and edge constraints. International Society for Magnetic Resonance in Medicine, p. 4308, 2012.**F. Lam**, J. P. Haldar, and Z.-P. Liang. Motion compensation for reference-constrained image reconstruction from limited data. IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp. 73-76, 2011.**F. Lam**, R. Subramanian, D. Xu, and K. F. King. Incorporating support constraints for sparse regularization reconstruction. International Society for Magnetic Resonance in Medicine, p. 2843, 2011.**F. Lam**, D. Hernando, K. F. King, and Z.-P. Liang. Compressed sensing reconstruction in the presence of a reference image. International Society for Magnetic Resonance in Medicine, Stockholm, Sweden, p. 4861. 2010.