CONFERENCE PROCEEDINGS

As a PI

  • Y. Li, Z. Wang, A. Anderson, R. Zhao, P. Arnold, G. Huesmann, F. Lam, Fast MRSI reconstruction combining linear and nonlinear manifold models, Proc. of ISMRM, 2023, p.0870.
  • Y. Wang, S. S. Rubakhin, F. Lam, High-resolution 1H-MRSI of the brain at 9.4T integrating relaxation enhancement and subspace imaging, Proc. of ISMRM, 2023, p.3691.
  • R. Zhao, X. Peng, F. Lam, Integrating Adaptive Generative Network and Subspace Models for Accelerated MR Parameter Mapping, Proc. of ISMRM, 2023, p.1628.
  • R. Zhao, Y. Li, Z. Wang, A. Anderson, P. Arnold, G. Huesmann, F. Lam, MR spatiospectral reconstruction using plug&play denoiser with self-supervised training, Proc. of ISMRM, 2023, p.0955.
  • Z. Wang, Y. Li, F. Lam, Whole-brain multi-parametric molecular imaging using accelerated J-resolved subspace 1H-MRSI, In Proc. of ISMRM, 2023, p.3682.
  • Z. Wang, Y. Li, F. Lam, High-Resolution brain metabolite T2 mapping using optimized multi-TE MRSI, In Proc. of ISMRM 2022, p. 4998.
  • Z. Wang, F. Lam, Fast volumetric diffusion-weighted MRSI: improved acquisition and data processing, In Proc. of ISMRM 2022, p. 3524.
  • F. Lam, Y. Li, Y. Zhao, J. Haldar, Improving lipid suppression for 1H-MRSI using region-optimized virtual coils, In Proc. of ISMRM 2022, p. 2621.
  • X. Ye, Z. Wang, F. Lam, Improved nuisance signal removal for 1H MRSI using a low-rank plus sparse model with learned subspaces, In Proc. of ISMRM 2022, p. 4315.
  • F. Lam, H. Hetherington, and J. Pan, Rapid MRSI of the brain on 7T using subspace-based processing, Annual Meeting of International Society for Magnetic Resonance in Medicine, 2021, p. 2206.
  • Y. Li, L. Ruhm, A. Henning, F. Lam, LeaRning nonlineAr representatIon and projectIon for faSt constrained MRSI rEconstruction (RAIISE), In Proc. of ISMRM 2022, p. 4808.
  • Y. Li, Z. Wang, F. Lam, High-SNR J-Resolved MRSI by jointly learning nonlinear representation and projection, In Proc. of ISMRM 2022, p. 3560.
  • Z. Wang and F. Lam, High resolution volumetric diffusion-weighted MRSI using a subspace approach, Annual Meeting of ISMRM, 2021, p. 37.
  • Y. Li, Z. Wang, and F. Lam, SNR-enhancing reconstruction for multi-TE MRSI using a learned nonlinear low-dimensional model, Annual Meeting of ISMRM in Medicine, 2021, p. 1998.
  • Z. Wang, Y. Li, and F. Lam, Optimized subspace-based J-resolved MRSI for simultaneous metabolite and neurotransmitter mapping, Annual Meeting of ISMRM, 2021, p. 72.
  • Y. Li, Z. Wang, F. Lam, Separation of metabolites and macromolecules for short-TE 1H-MRSI using learned nonlinear models, IEEE International Symposium on Biomedical Imaging, 2020, pp. 1725-1728.
  • Z. Wang, F. Lam, B0 inhomogeneity corrected reconstruction for low-resolution J-resolved MRSI using low-rank and spatial constraints, Annual Meeting of ISMRM, 2020, p. 2911.
  • R. Ho, F. Lam, High-resolution 3D spin-echo MRSI using interleaved water navigators, sparse sampling and subspace-based processing, Annual Conference of IEEE Engineering in Medicine and Biology Society, 2020.
  • Y. Li, Z. Wang, F. Lam, Separation of metabolites and macromolecules for short-TE 1H-MRSI using learned nonlinear models, Annual Meeting of ISMRM, 2020, p. 2854.
  • Y. Li, X. Peng, F. Lam, Learning nonlinear low-dimensional models for MR spectroscopic imaging using neural networks, Annual Meeting of ISMRM, 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 ISMRM, 2019, p. 1257.

As a trainee

  • 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.