Software

GrOpt Toolbox

• The toolbox allows for gradient waveforms to be designed that better utilize available gradient hardware performance, while allowing for additional constraints to be flexibly added to control for a range of desired performances. Additionally, the optimization has been fine-tuned to operate in real-time, allowing for flexible implementation on vendor-agnostic scanner hardware for on-the-fly usage.
• Loecher M, Middione MJ, Ennis DB. A Gradient Optimization (GrOpt) Toolbox for General Purpose Time-Optimal MRI Gradient Waveform Design. Magn Reson Med. Accepted May 2020. 10.1002/mrm.28384
• Middione MJ, Loecher M, Moulin K, Ennis DB. Optimization Methods for Magnetic Resonance Imaging Gradient Waveform Design. NMR Biomed. 2020 Apr 27:e4308. doi: 10.1002/nbm.4308. [Epub ahead of print] PMID: 32342560
• https://github.com/cmr-group/gropt/tree/master

Tag Tracking CNN and Synthetic Cardiac Motion Generator

• This repository contains a synthetic data generator used to create large training datasets for machine learning based studies of motion in MRI.
• Additionally, a deep learning based approach for tag tracking is provided that uses the synthetic data for training, which remains highly accurate when transferring to in vivo data.
• Loecher M, Perotti LE, Ennis DB. Using synthetic data generation to train a cardiac motion tag tracking neural network. Medical Image Analysis. 2021 Dec 1;74:102223. doi: 10.1016/j.media.2021.102223. PMID: 34555661
• https://github.com/mloecher/tag_tracking
  

Diffusion Recon

• This repository contains a matlab framework for reconstructing diffusion model for diffusion MRI.
• https://github.com/KMoulin/DiffusionRecon

Heart Rate Simulator

• This repository contains a cross platform (Matlab and Python) script that creates an artificial trigger, based off user input parameters, that writes to an Arduino Uno importable file.
• https://github.com/tecork/HR-Sim

3D DENSE Plugin for Right Ventricle

• This DENSEanalysis affiliate plugin for analyzing 3D Cine displacement encoding with stimulated echoes (DENSE) MRI data of a crescent-shaped organ.
• https://github.com/Zhan-Qiu-Liu/DENSE3D_Plugin_4CrescentOrgan

Non-Convex Velocity Solver for Phase Contrast MRI Data

• This code is meant to accompany the reconstruction described in "Velocity Reconstruction with Non-Convex Optimization for Low-VENC Phase Contrast MRI." The velocity solver itself is written in C++, accompanying code to set up the example datasets and run the solver is written in Python.
• Loecher M, Ennis DB. Velocity reconstruction with nonconvex optimization for low-velocity-encoding phase-contrast MRI. Magn Reson Med. 2018;80(1):42-52. PMID: 29130519
• https://github.com/mloecher/nc_vel_solver

Convex Optimized Gradient Waveform Design for 4D Flow MRI*

• This repository contains sample code to use for generating convex optimized waveforms for 4D-Flow MRI.

• Loeccher M, Magrath P, Aliotta E, Ennis DB. Time-optimized 4D phase contrast MRI with real-time convex optimization of gradient waveforms and fast excitation methods. Magn Reson Med. 2019;82(1):213-224. PMID: 30859606
• https://github.com/mloecher/cvxflow

4D Laplacian Phase Unwrapping for 4D Flow MRI

• This Matlab code accompanies the manuscript below to allow the user to reproduce the results from the digital phantom experiment.
• Loecher M, Schrauben E, Johnson KM, Wieben O. Phase unwrapping in 4D MR flow with a 4D single-step laplacian algorithm. J Magn Reson Imaging. 2016;43(4):833-42. PMID: 26417641
• https://github.com/mloecher/4dflow-lapunwrap

Cardiac Kinematics Phantom

• This code simulates mid left ventricular motion in an analytical phantom and generate corresponding DENSE data.
• Verzhbinsky IA, Perotti LE, Moulin K, Cork TE, Loecher M, Ennis DB. Estimating Aggregate Cardiomyocyte Strain Using In Vivo Diffusion and Displacement Encoded MRI. IEEE Trans Med Imaging. 2019 Aug. PMID: 31398112
• https://github.com/luigiemp/CardiacKinematicsPhantom

Convex Optimized Diffusion Encoding (CODE)*

• Optimizations for Convex Optimized Diffusion Encoding (CODE) for Diffusion Weighted MRI.
• Aliotta E, Moulin K, Ennis DB. Eddy current-nulled convex optimized diffusion encoding (EN-CODE) for distortion-free diffusion tensor imaging with short echo times. Magn Reson Med. 2018;79(2):663-672. PMID: 28444802
• https://github.com/ealiotta/code-gradient-design

Eddy Current Nulled Convex Optimized Diffusion Encoding (EN-CODE)*

• Optimizations for Eddy Current Nulled Convex Optimized Diffusion Encoding (EN-CODE) for Diffusion Weighted MRI with reduced distortions.
• Aliotta E, Wu HH, Ennis DB. Convex optimized diffusion encoding (CODE) gradient waveforms for minimum echo time and bulk motion-compensated diffusion-weighted MRI. Magn Reson Med. 2017;77(2):717-729. PMID: 26900872
• https://github.com/ealiotta/encode-gradient-design

* For faster optimizations and/or direct b-value optimization, please use the GrOpt Toolbox.