CONFERENCE PROCEEDINGS

2019

  • Y. Li, X. Peng, F. Lam, Learning nonlinear low-dimensional models for MR spectroscopic imaging using neural networks, Annual Meeting of International Society for Magnetic Resonance in Medicine, 2019, p. 947.
  • F. Lam and B. Sutton, Efficient intravoxel B0 inhomogeneity corrected reconstruction of multi-gradient-echo images using a low-rank encoding operator, Annual Meeting of International Society for Magnetic Resonance in Medicine, 2019, p. 1257.

Until 2018

  • F. Lam, Y. Li, R. Guo, B. Clifford, X. Peng, Z.-P. Liang, Further accelerating SPICE for ultrafast MRSI using learned spectral features, Annual Meeting of International Society for Magnetic Resonance in Medicine, 2018, p. 1058.
  • F. Lam, B. Cheng, Z.-P. Liang, Accelerated J-resolved MRSI using joint subspace and sparsity constraints, Annual Meeting of International Society for Magnetic Resonance in Medicine, Honolulu, 2017, p. 1202.
  • F. Lam, Y. Li, Bryan Clifford, X. Peng, Z.-P. Liang, Simultaneous mapping of brain metabolites, macromolecules and tissue susceptibility using SPICE, Annual Meeting of International Society for Magnetic Resonance in Medicine, Honolulu, 2017, p. 1249.
  • F. Lam, Y. Li, B. Clifford, Z.-P. Liang, Macromolecule mapping with ultrashort-TE acquisition and metabolite spectral prior, Annual Meeting of International Society for Magnetic Resonance in Medicine, Honolulu, 2017, p. 5518.
  • C. Ma, F. Lam, Q. Liu, and Z.-P. Liang, Accelerated High-Resolution Multidimensional 1H-MRSI Using Low-Rank Tensors, Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016, pp. 379.
  • F. Lam, H. Lu, Y. Yang, B. Clifford, C. Ma, G. E. Robinson, and Z.-P. Liang. Ultrahigh-resolution metabolic imaging at 9.4 Tesla. Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016, p. 385.
  • C. Ma, F. Lam, Q. Ning, B. A. Clifford, Q. Liu, C. L. Johnson, and Z.-P. Liang, High-Resolution Dynamic 31P-MRSI Using High-Order Partially Separable Functions, Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016, pp. 875.
  • B. Clifford, F. Lam, Q. Liu, C. Ma, and Z.-P. Liang. SENSing-SPICE: Integrating parallel imaging with subspace-based 3D 1H-MRSI. Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016, p. 1212.
  • M. Sheikh, F. Lam, C. Ma, B. Clifford, and Z.-P. Liang, FID acquisition-based rapid high-resolution 3D 1H-MRSI of the brain. 2016 Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, p. 1681.
  • F. Lam, C. Ma, Q. Liu, B. Clifford, and Z.-P. Liang. Achieving high spatiotemporal resolution for 1H-MRSI of the brain. 2016 Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, p. 2356.
  • Q. Ning, C. Ma, F. Lam, B. Clifford, and Z.-P. Liang. Removal of nuisance signal from sparsely sampled 1H-MRSI data using physics-based spectral bases. Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016, p. 2361.
  • Q. Ning, C. Ma, F. Lam, B. Clifford, and Z.-P. Liang. Spectral quantification of MRSI data using spatio-spectral constraints. Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016.
  • F. Lam, Q. Ning, C. Ma, B. Clifford, and Z.-P. Liang. 3D Metabolite and neurotransmitter mapping using multiple-TE encoding with sparse sampling. Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016, p. 3182.
  • C. Ma, F. Lam, Q. Ning, B. A. Clifford, R. Larsen, and Z.-P. Liang, A subspace-based approach to high-resolution 31P-MRSI. Annual Meeting of International Society for Magnetic Resonance in Medicine, Singapore, 2016, p. 3956.
  • C. Ma, F. Lam, Q. Ning, C. L. Johnson, and Z.-P. Liang. High-resolution 1H-MRSI of the brain using short-TE SPICE. In Proc. International Society for Magnetic Resonance in Medicine, Toronto, 2015, p. 992.
  • F. Lam, B. Clifford, C. Ma, C. L. Johnson, and Z.-P. Liang. Ultra-high resolution 3D 1H-MRSI of the brain: Subspace-based data acquisitions and processing. Annual Meeting of International Society for Magnetic Resonance in Medicine, Toronto, 2015, p. 2370.
  • 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.
  • C. Ma, F. Lam, C. Johnson, and Z.-P. Liang. Removal of nuisance lipid signals from limited k-space data in 1H MRSI of the brain. Annual Meeting of International Society for Magnetic Resonance in Medicine, Milan, Italy, 2014, p. 2887.
  • F. Lam, C. Ma, T. K. Hitchens, C. Johnson, C. Ho, and Z.-P. Liang. A subspace approach to high-resolution spectroscopic imaging: In vivo experimental results. Annual Meeting of International Society for Magnetic Resonance in Medicine, Milan, Italy, 2014, p. 2894.
  • Wu, F. Lam, C. Ma, and Z.-P. Liang. Improved image reconstruction for subspace-based spectroscopic imaging using non-quadratic regularization. In Proc. IEEE Engineering in Medicine and Biology Society, pp. 2432-2435, 2014.
  • 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.