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Fan Lam
Associate Professor
,
Bioengineering
Director, M.S. in Biomedical Image Computing Program
,
Bioengineering
Associate Professor
,
Electrical and Computer Engineering
Associate Professor
,
Neuroscience Program
Associate Professor
,
Biomedical and Translational Sciences
Associate Professor
,
Beckman Institute for Advanced Science and Technology
Affiliate, Personalized Nutrition Initiative
,
Carl R. Woese Institute for Genomic Biology
Email
fanlam1
illinois
edu
Overview
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Research & Scholarship
(65)
Datasets
(2)
Honors
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Dive into the research topics where Fan Lam is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Keyphrases
MR Spectroscopic Imaging (MRSI)
100%
High-resolution
85%
Image Reconstruction
77%
Imaging Data
54%
Magnetic Resonance Imaging
53%
MR Spectroscopic Imaging
51%
Sparsity Constraint
47%
1H-MRS
42%
Sparse Sampling
34%
Spectroscopic Imaging
31%
Spices
29%
Denoising
27%
Diffusion-weighted Image
26%
Macromolecules
26%
Subspace Methods
24%
Low-rank Constraint
24%
Subspace Model
24%
Edge Constraint
22%
Magnetic Resonance Image Reconstruction
22%
Subspace Approach
22%
Mass Spectrometry Imaging
22%
MR Image Reconstruction
22%
Optimization Problem
21%
Compressed Sensing
21%
Signal-to-noise Ratio
21%
Undersampled Data
20%
Undersampling
20%
Low-rank Tensor
20%
Parameter Mapping
19%
Parameter Estimation
19%
MR Parameter Mapping
18%
Target Image
18%
Partially Separable Functions
17%
Metabolic Imaging
17%
Denoising Diffusion
16%
Partial Separability
16%
T2 Mapping
15%
Spatial Constraints
15%
Cine Cardiac MRI
14%
Dynamic Imaging
14%
Rank Constraint
14%
Spectral-spatial Feature
14%
Nonlocal Operators
14%
Patch-based
14%
Reference Dependence
14%
Deep Learning
14%
Spectral Quantification
14%
Low-dimensional Models
14%
Low-rank Filtering
14%
Ultrafast
14%
Engineering
Image Reconstruction
94%
High Resolution
85%
Sparsity
59%
Regularization
48%
Joints (Structural Components)
34%
Compressed Sensing
33%
SPICE
29%
Simulation Result
26%
Signal-to-Noise Ratio
26%
Parameter Estimation
26%
Space Data
26%
Signal Model
24%
Separability
24%
Rank Tensor
22%
Optimisation Problem
21%
Dimensional Subspace
21%
Target Image
20%
Image Model
19%
Similarities
17%
Reference Image
16%
Experimental Result
16%
Dimensional Image
16%
Spectral Information
14%
Harmonics
14%
Alternating Direction Method of Multipliers
14%
Illustrates
13%
Denoising Problem
12%
Fourier Transform
12%
Spectral Distribution
11%
Conventional Method
11%
Autoencoder
11%
Acquisition Time
11%
Data Model
9%
Temporal Resolution
9%
Spatial Resolution
9%
Dynamic Contrast
9%
Basis Function
9%
State-of-the-Art Method
9%
Image Sequence
9%
Noisy Data
8%
Processing Strategy
8%
Penalty Function
7%
Noise Ratio
7%
Dimensional Model
7%
Nonlinear Model
7%
Relative Stability
7%
Motion Compensation
7%
Eluting Stent
7%
Spectral Estimation
7%
Spectral Feature
7%
