See LICENSE file for licensing information.

-------------------------------------------------------------------------------


The tools in this software implement various reconstruction algorithms. 
Please cite the corresponding articles when using these tools for research.
Some references can be found at the end of this file. The source code might
provide more detailed references, e.g. for specific iterative algorithms.



1. Help
=======

Please direct all questions or comments to the public mailing list:

	mrirecon@lists.eecs.berkeley.edu

	https://lists.eecs.berkeley.edu/sympa/info/mrirecon


Note: This list has a public archive! Please do not send
any confidential information.



Updates and further information can be found here:

	http://mikgroup.github.io/bart/




2. Installation
===============

2.1. Prerequisites

GCC compiler, the FFTW, GSL (or ACML) libraries and optionally 
a CUDA Implementation (see recon/Makefile to turn these
options on or off)

The software can be used in combination with Matlab or octave.


Note: In the following, the symbol '$' indicates a shell prompt.
Do not type '$' when entering commands.



2.1.1. Linux

The software tools in recon should run on any recent Linux distribution.

To install the required libraries on Debian and Ubuntu run:

$ sudo apt-get install build-essential libfftw3-dev libgsl0-dev liblapack-dev

(optional)
$ sudo apt-get install octave

(optional)
install the ISMRM Raw Data format library (http://ismrmrd.sourceforge.net/).



2.1.2. Mac OS X

Xcode is required and it is recommended to install a newer version 
of gcc (4.7 seems to work) from MacPorts (http://www.macports.org/).


$ sudo port install fftw-3-single
$ sudo port install gsl
$ sudo port install gcc47

(optional)
$ sudo apt-get install octave

(optional)
install the ISMRM Raw Data format library (http://ismrmrd.sourceforge.net/).



2.1.3. Windows

You can use BART on Windows using Cygwin:

https://www.cygwin.com/

Install Cygwin and select the following packages:

Devel: gcc, make
Math: fftw3, fftw3-doc, libfftw3-devel, libfftw3_3
Math: liblapack-devel, liblapack-doc, liblapack0
Libs: gsl, gsl-apps, gsl-devel, gsl-doc


Then use the cygwin shell to compile BART as described below.


(An alternative to using Cygwin is a virtual machine with Linux.)



2.2. Downloading and Compilation


If you are a git user, you can simply clone our public repository:

$ git clone https://github.com/mikgroup/bart


Otherwise, please download the latest version as a zip file
from Github:

	http://github.com/mikgroup/bart/releases/latest

and unpack it somewhere on your computer.


Open a terminal window and enter the bart directory (the top-level
directory with the Makefile in it). To build the reconstruction
tools type:

$ make



If you have installed the ismrmrd library, you can also
build the ISMRM raw data import tool:

$ make ismrmrd








2.3. Getting Started

2.3.1. Organization


.		main directory / built software tools
Makefile	Makefile
matlab/		Matlab helper scripts
python/		Python helper functions
doc/		documentation
src/		source code
src/calib 	source code for sensitivity calibration
src/sense	source code for SENSE or ESPIRiT reconstruction
src/noir	source code for nonlinear inversion
src/sake	source code for SAKE reconstruction
src/wavelet2	source code for wavelets
src/wavelet3	source code for new wavelets (experimental)
src/num		base library with numerical functions
src/iter	iterative algorithms
src/linops	library of linear operators
src/misc	miscellaneous (e.g. I/O)
src/ismrm	support for ISMRM raw data format
lib/		built software libraries




2.3.2. Terminal

When using the toolbox commands from a UNIX shell, it is recommended
to set the TOOLBOX_PATH to the base directory and to add it to
the PATH variable. You can do this by running the following command:

$ . vars.sh

Note: The dot or 'source' command is needed so that the variables
are imported into the current shell.


2.3.3. Matlab

You can set the TOOLBOX_PATH to the base directory and to add it
to the Matlab path by running the following command in the
bart directory:

>> vars

(Note: The '>>' indicates the shell prompt. Do not type '>>'
when entering commands.)



You can use Matlab to read and visualize/process files. To write
a data file 'xyz' from Matlab you can run:

>> writecfl('xyz', A);


Note, that the name 'xyz' is used without filename extension.
See below for more information about the file format used in BART.

To read the data file 'xyz' back into Matlab use:

>> A = readcfl('xyz');


To call a BART tool (e.g. ecalib) from Matlab, you can use the
'bart' command:

>> sensitivities = bart('ecalib', kspace);



Download and unpack the examples which demonstrate interoperability
with Matlab. Go to the examples directory and run:

>> examples







3. Data Format
==============

3.1. Generic

The input and output datasets are each stored in a pair of files: one
header (*.hdr) and one raw data (*.cfl). The header is a simple text
readable file that describes the dimensions of the data. The raw data
file is a binary file containing a single contiguous block of array
data of dimensions described in the header stored in column-major order
(first index is sequential). The raw data file is complex float 
(32 bit real + 32 bit imaginary, IEEE 747 binary32 little-endian).

Convenience methods to read and write our data files using Matlab may
be found in recon/matlab (readcfl.m and writecfl.m).



3.2. Magnetic Resonance Imaging Data

For MRI data and images, the dimensions are usually assigned in
the following order:

0 readout
1 phase-encoding dimension 1
2 phase-encoding dimension 2
3 receive channels
4 ESPIRiT maps
...
...

(more dimensions are defined in src/misc/mri.h)


Undersampled data is stored with with zeros in the unsampled
positions.



3.3. Non-Cartesian Trajectories and Samples

The k-space coordinates for each sample are stored along dimension 0
which must have size equal to three. The unit of measurement is 1/FOV.
Dimension 1 stores the samples along a single readout windows while
dimension 2 may be used to differentiate between different lines
(e.g. radial spokes). Channel (3) and map (4) dimensions must not
be used (i.e. have size one), while other dimensions can be used
as for Cartesian data. Non-Cartesian samples are stored in a similar
way as trajectories except that dimension 0 is not used. The channel
dimension can be used for different receiver coils as usual.




4.. Command-line Tools
======================

All tools operate on the simple file format given above. Indices and
dimensions run from 0 to N-1. Sometimes a set of dimensions is given
as a bitmask where the lowest bit corresponds to the 0st dimension.


For example, an inverse Fourier transform of first three dimensions can
be performed with the following command:


$ fft -i 7 kspace volume


More information about each command can be found in 'doc/commands.txt'.





5. References
=============


Uecker M, Ong F, Tamir JI, Bahri D, Virtue P, Cheng JY, Zhang T, Lustig m,
Berkeley Advanced Reconstruction Toolbox, Annual Meeting ISMRM, Toronto 2015
In: Proc Intl Soc Mag Reson Med 23:2486 (accepted)


Uecker M, Virtue P, Ong F, Murphy MJ, Alley MT, Vasanawala SS, Lustig M,
Software Toolbox and Programming Library for Compressed Sensing and
Parallel Imaging, ISMRM Workshop on Data Sampling and Image
Reconstruction, Sedona 2013


References related to implemented methods and algorithms can be
found in the file 'doc/references.txt'.