Distributed Code

Please click the link below the description for instructions on accessing the code.

MRFIL has a Github page with shared software

Please see our Github page for our shared software, including 

  • PowerGrid from ISMRM 2016 – GPU and MPI accelerated iMRI image reconstruction
  • LesionMapper from ISMRM 2015 – For fully automated lesion quantification in MS
  • GPU IMPATIENT code – GPU accelerated image reconstruction code from 2013

Fully Automated White Matter Hyperintensity Lesion Mapping using FSL

We have developed a lesion mapper script using FSL that can measure and label lesion volumes automatically 

This work is described in our ISMRM abstract: 
N. C. P. Wetter, E. A. Hubbard, R. W. Motl, B. P. Sutton. Fully-automated single-image T2 white matter hyperintensity mapping and quantification with FSL. Intl Soc. Magn Reson Med, 2015. p. 1408. (Traditional Poster, Monday, Multiple Sclerosis Section)

And our paper
Wetter NC, Hubbard EA, Motl RW, Sutton BP. Fully automated open-source lesion mapping of T2-FLAIR images with FSL correlates with clinical disability in MS. Brain Behav. 2016 Jan 28;6(3):e00440. doi: 10.1002/brb3.440. eCollection 2016 Mar. https://pubmed.ncbi.nlm.nih.gov/26855828/

GPU accelerated MRI reconstruction including magnetic field inhomogeneity, non-Cartesian trajectories, parallel imaging, and image regularization

We have developed code called the “Illinois Massively Parallel Acceleration Toolkit for Image reconstruction with ENhanced Throughput in MRI (IMPATIENT MRI). This toolkit accomodates non-Cartesian trajectories, parallel imaging, field inhomogeneity, and various regularization penalties. All while it speeds reconstruction time up to a factor of 100 or more compared to accelerated CPU code. 

This work is described in our latest publication: 
* Gai J, Obeid N, Holtrop JL, Wu XL, Lam F, Fu M, Haldar JP, Hwu WM, Liang ZP, Sutton BP. More IMPATIENT: A Gridding-Accelerated Toeplitz-based Strategy for Non-Cartesian High-Resolution 3D MRI on GPUs. J Parallel Distrib Comput. 2013 May 1;73(5):686-697. Link to pubmed entry

Human Physiology Systems Simulation Models

With support from Mathworks, we adapted several human physiology simulation models to enable better visualization of the simulation. There are modules on neurophysiology, cardiovascular physiology, muscle, and endocrinology. The visual representation of differential equations in Simulink allows student to visualize the overall system function, while maintaining the mathematical and quantitative nature of the model. Work is available as courseware through the Classroom Resources site of Mathworks or at the link below