Michael Lustig
Radiology, Nuclear Medicine and Imaging · 2006–2017
A researcher in the Science corpus: 9 papers; trusts 35 researchers and is trusted by 103 researchers here, as inferred from the citation graph.
Subfields
- Radiology, Nuclear Medicine and Imaging — 36 citations into it; #38 of 3,265 by trust here, #116 by citations
- Computational Mechanics — 31 citations into it; #409 of 10,001 by trust here, #248 by citations
- Computer Vision and Pattern Recognition — 30 citations into it
- Atomic and Molecular Physics, and Optics — 16 citations into it; #189 of 7,135 by trust here, #809 by citations
- Statistics and Probability — 13 citations into it
- Optimization & Training — 10 citations into it
- Signal Processing — 8 citations into it
- Applied Mathematics — 7 citations into it
Whom Michael Lustig trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David L. Donoho
- E.J. Candes
- Justin K. Romberg
- Bradley P. Sutton
- Jeffrey A. Fessler
- Yaakov Tsaig
- Scott Shaobing Chen
- Michael Elad
- Terence Tao
- Jean-Luc Starck
Who trusts Michael Lustig overall
- David L. Donoho
- Justin P. Haldar
- Florian Knoll
- Saiprasad Ravishankar
- Joshua D. Trzasko
- Yan Yang
- Li Feng
- Rick Chartrand
- Tran Minh Quan
- Mark Murphy
Papers from Michael Lustig's perspective
Ordered by how strongly the researchers Michael Lustig trusts endorse each paper. Same corpus, a different order for every researcher.
- Regression Shrinkage and Selection via the Lasso
- Atomic Decomposition by Basis Pursuit
- Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information
- Stable signal recovery from incomplete and inaccurate measurements
- The Elements of Statistical Learning
- 双対平坦空間におけるLeast Angle Regressionと情報量規準
- For most large underdetermined systems of linear equations the minimal 𝓁1‐norm solution is also the sparsest solution
- Stable recovery of sparse overcomplete representations in the presence of noise
- An iterative thresholding algorithm for linear inverse problems with a sparsity constraint
- A new approach to variable selection in least squares problems
Their papers
- Better than real: Complex-valued neural nets for MRI fingerprinting (2017) — 196 citations
- ESPIRiT — An Eigenvalue Approach to Autocalibrating Parallel MRI: Where SENSE meets GRAPPA (2014) — 1,557 citations
- Coil Compression for Accelerated Imaging with Cartesian Sampling (2012) — 310 citations
- Fast ℓ1-SPIRiT Compressed Sensing Parallel Imaging MRI: Scalable Parallel Implementation and Clinically Feasible Runtime (2012) — 314 citations
- SPIRiT: Iterative Self-consistent Parallel Imaging Reconstruction from Arbitrary k-Space (2010) — 926 citations
- Compressed Sensing MRI (2008) — 2,351 citations
- An Interior-Point Method for Large-Scale $\ell_1$-Regularized Least Squares (2007) — 1,886 citations
- Sparse MRI: The application of compressed sensing for rapid MR imaging (2007) — 7,475 citations
- k-t SPARSE: High frame rate dynamic MRI exploiting spatio-temporal sparsity (2006) — 391 citations