BRAIN Lab · Software
Software
Open-source code, data and pulse sequences from our group.
(Siemens VE11C, VE11E, XA30A, XA61A-SP01) pulse sequences
High resolution diffusion imaging with gSlider-SMS
Machine learning
Zero-shot Prior Learning of Spatio-temporal Multi-echo/contrast MRI Reconstruction with Iterative Refinement
Quantifying the uncertainty of neural networks using Monte Carlo dropout for safer and more accurate deep learning based quantitative MRI
MAPLE: Accelerated MR Parameter Mapping with Scan-specific Unsupervised Networks
Latent Signal Modeling (LSM): Learning compact latent representations of signal evolution for improved shuffling reconstruction
Rapid quantitative imaging with Wave-MODL and joint reconstruction
Wave-MODL: Wave-Encoded Model-Based Deep Learning
eRAKI: Fast Robust Artificial neural networks for K‐space Interpolation
Scan-specific, Parameter-free Artifact Reduction in K-space (SPARK)
Accelerated Multi-shot EPI through Machine Learning and Joint Reconstruction
Distortion-free Echo Planar Imaging
VUDU-SAGE: Efficient T2 and T2* Mapping using Joint Reconstruction for Motion-Robust, Distortion-Free, Multi-Shot, Multi-Echo EPI
VUDU: motion-robust, distortion-free multi-shot EPI
T2-BUDA-gSlider: rapid high resolution T2 mapping with blip-up/down acquisition, gSlider and subspace reconstruction
Parallel imaging and compressed sensing
VC-MUSSELS: Hankel low-rank regularization for multi-shot EPI with virtual coils for high-fidelity partial Fourier reconstruction
Calibrationless parallel imaging for multi echo/contrast data
Joint Reconstruction
Bayesian sensitivity encoding enables parameter-free, highly accelerated joint multi-contrast reconstruction
Joint SENSE for faster multi-contrast imaging
J-LORAKS and JVC-GRAPPA: Improving parallel imaging by jointly reconstructing multi-contrast data
Joint L1-SPIRiT reconstruction for phase-cycled balanced SSFP
Joint GRAPPA reconstruction for phase-cycled balanced SSFP
Multicontrast reconstruction with Bayesian Compressed Sensing
Bayesian Compressed Sensing reconstruction with prior estimate
Wave-CAIPI
CS-Wave reconstruction with automated parameter selection
Simultaneous Time Interleaved MultiSlice (STIMS) with Compressed Sensing Wave
Wave-CAIPI for Simultaneous MultiSlice RARE/Turbo Spin Echo
Wave-CAIPI for highly accelerated 3D Gradient Echo imaging
Receiver coil combination without reference data
Block Coil Compression (BCC) for reference-free coil combination at ultra high field
SVD for reference-free coil combination at high field
Quantitative Susceptibility Mapping (QSM)
Harmonized QSM post-processing pipeline for multi-echo GRE data, particularly at 7T
Dipole Inversion Algorithms
BM4D QSM
Nonlinear Dipole Inversion (NDI) enables robust QSM
Fast Total Generalized Variation regularized QSM
Multi-orientation COSMOS QSM and Susceptibility Tensor Imaging
Fast l1-Regularized QSM with Magnitude Weighting and SHARP background filtering
l1- and l2-Regularized QSM and PDF background filtering
Closed-form l2-Regularized QSM
Single-Step QSM
with Total Generalized Variation regularization
with l2-Regularization
Demos and Recon Challenges
Data and code for the QSM Reconstruction Challenge 2.0
ISMRM demo including Fast Algorithm for Nonlinear Susceptibility Inversion (FANSI)
Data and code for the QSM Reconstruction Challenge 1.0
MR Spectroscopic Imaging
Fast lipid suppression with l2-regularization
Lipid suppression with spatial priors and l1-regularization
Accelerated Diffusion Spectrum Imaging
Fast Diffusion Spectrum Imaging reconstruction with trained dictionaries
Diffusion Spectrum Imaging with dictionary reconstruction