BART: Tutorials, Workshops & Webinars

Quick Links: Home, Download & Installation, Tutorials, Webinars, List of Features, References & Reproducibility

bart logo reconstructed from k-space

Figure: Simulated MRI images.

This webpage includes BART documentary and educational materials that were published over the last few years in tutorials, workshops and online webinars. It is organized by topics, starting with the basic material for new users, and moving to advanced materials.

Table of contents

Getting Started with BART
1. Linux/unix terminal
2. Python
3. Matlab

Non-Cartesian Reconstruction
1. Non-Cartesian SENSE reconstruction
2. GRASP reconstruction

Model-based Reconstruction
1. Subspace-constrained reconstruction
2. Model based reconstruction

Dynamic MRI Reconstruction
1. Introduction to dynamic MRI reconstruction with BART
2. Dynamic Contrast Enhanced (DCE) MRI

Deep Learning with BART
1. Introduction to machine learning reconstruction with BART
2. Machine learning reconstruction with BART
3. TensorFlow and deep learning reconstruction with BART

SENSE reproducibility challenge
The BART solution of the SENSE reproducibility challenge

More useful links
The 2020-2022 webinar series

Getting Started with BART

1. Terminal

1.1 Using BART through the linux/unix command line: webinar for new users (2020)

This two-days webinar (from June 2020) introduced the concepts of working with BART through the linux/unix command line.

Day 1

Day 2

1.2 Bart workshop - ISMRM 2019

The workshop tutorial included an introduction to the BART command-line tools. Topics covered:

1.3 Bart workshop - ISMRM 2016

The workshop included demos for:

2. Python

2.1 Webinar for new users - python

The webinar we had on July 2021 includes a demo and hands-on exercise for working with BART in a python environment. It covers:

2.2 Getting started with BART - 45min tutorial

The ESMRMB MRI-Together 2021 workshop included a demo and hands-on exercise for working with BART in a python environment. It covers:

2.3 Data processing and computing g-factor for parallel imaging

The ISMRM 2019 workshop included a tutorial that shows how to use the BART-Python interface for:

3. Matlab

Matlab Interface and Examples

The toolbox can also be used in combination with Matlab/Octave.

 >> sensitivities = bart('ecalib', kspace);
 >> image_out = bart('pics -l1 -r0.001', kspace, sensitivities);

More examples where the tools are called directly from Matlab can be found here.

Matlab code and data: GitHub repository

A Matlab-based image viewer which works well with BART is arrayShow by Tilman Sumpf.

3.1 Inroduction to the BART-Matlab interface

The first webinar of 2020 included a demo for using the BART Matlab API.

Webinar #1 Recordings

Webinar #1 Materials

3.2 Using the BART-Matlab interface

The ISMRM 2016 workshop included a demo for performing a Wave-CAIPI reconstruction followed by a retrospective Wave-CS reconstruction tool with the BART Matlab API.

Workshop Material


Non-Cartesian Reconstruction with BART

1. Linux/unix terminal

1. Non-Cartesian SENSE reconstruction

The ISMRM 2019 workshop included a demo for non-Cartesian SENSE reconstruction

Workshop Material

2. GRASP reconstruction

The ISMRM 2016 workshop included a demo for GRASP reconstruction from golden-ratio radial k-space sampling.

Workshop Material


Model-based Reconstruction with BART

1. Subspace constraint reconstruction & model-based reconstruction

The webinar of March 2021 included demos and hands-on tutorials for:

Webinar #3 Recordings

Webinar #3 Materials

2. Model based reconstruction

The ISMRM 2021 BART software tutorial included an interactive demo on nonlinear model-based reconstruction for quantitative MRI (T1 mapping, water-fat separation)

Jupyter notebook


Dynamic MRI Reconstruction with BART

1. Introduction to dynamic MRI with BART

The webinar of Dec 2020 included demos and hands-on tutorials for:

Webinar #2 Recordings

Webinar #2 Materials

2. Dynamic Contrast Enhanced (DCE) MRI reconstruction

The ISMRM 2016 software demo included a tutorial on dynamic axial-slice reconstruction with BART.

Jupyter notebook

3. GRASP reconstruction

The ISMRM 2016 workshop included a demo for GRASP reconstruction from golden-ratio radial k-space sampling.

Workshop Material


Deep Learning with BART

1. Introduction to machine learning reconstruction with BART

BART webinar #6 (March 1, 2022) included demos and hands-on tutorials for working with BART in a python environment. It covers:

2. Machine learning reconstruction with BART

The ESMRMB MRI-Together 2021 workshop included a demo and hands-on exercise for working with BART in a python environment. It covers:

3. Tensorflow and neural networks with BART

The ISMRM 2021 BART tutorial included demos and hands-on tutorials for:

All ISMRM 2021 Materials


SENSE Reproducibility Challenge

The BART solution of the SENSE reproducibility challenge

The challenge was organized by the ISMRM. The BART solution was presented in our Dec 2020 webinar:

Webinar #2 Recordings

Webinar #2 Materials


More useful links

Our 2020-2022 webinars series can also be found here:

Webinar Recordings

Webinar Materials


Webinars & workshops material in chornological order

There are new tutorials from our Webinar which you can find in a GitHub repository.

ISMRM 2021 As part of the ISMRM 2021 meeting, we gave a demo of the new features of BART related to non-linear model-based reconstruction and deep learning integration.

ISMRM 2016 The toolbox was presented at the ISMRM 2016 Data Sampling and Image Reconstruction Workshop. This material was created for BART version 0.3.00 and later versions might have minor differences. Please check the README included with each release for up-to-date installation instructions.

Demo code and data: GitHub repository