BDP Add-ons

This page lists some utility functions which could be useful for data processing with BrainSuite Diffusion Pipeline (BDP). BDP is a part of BrainSuite and is geared towards analysis with diffusion MRI data. Most of the utilities listed here are developed using MATLAB R2012a and can be used with MATLAB, unless otherwise mentioned.

• Merge multiple set of diffusion datasets

• Eigen file (.eig) to NIfTI converter

• Converting scanner saved fieldmap to units of radians/sec

Eigen file (.eig) to NIfTI converter

eig2nifti converts .eig.nii.gz files saved by BDP to standard NIfTI-1 format. It takes .eig.nii.gz file as input and writes out corresponding eigenvector and eigenvalue files in standard NIfTI-1 format.

Download Link: eig2nifti.zip (Author: Chitresh Bhushan, Last Modified: Oct 9, 2013)

Syntax

eig2nifti(input_eig_file, output_base)

where, input_eig_file is a character array of input filename (.eig.nii.gz) and output_base is character array of file-prefix for output filenames. Following example shows eig2nifti in action and explains the output files:

>> eig2nifti('2467264c.dwi.RAS.correct.eig.nii.gz', '2467264c.tensor')
Reading eig file...Done
Saving files...
Saved V1 file: 2467264c.tensor.V1.nii.gz
Saved V2 file: 2467264c.tensor.V2.nii.gz
Saved V3 file: 2467264c.tensor.V3.nii.gz
Saved L1 file: 2467264c.tensor.L1.nii.gz
Saved L2 file: 2467264c.tensor.L2.nii.gz
Saved L3 file: 2467264c.tensor.L3.nii.gz

where L1 file contains the largest eigenvalues with corresponding eigenvector saved in V1 file. Similarly, L2 file contains the second largest eigenvalues with corresponding eigenvector saved in V2 file followed by L3 file and V3 file. All eigenvalue files (L1,L2,L3) are 3D volume while eigenvector files (V1,V2,V3) are 4D volume with last dimension containing the eigenvectors.

eig2nifti depends on several other functions which are included along with the download zip. All files should be added to the MATLAB path. See included sample_eig2nifti.m for another example of running eig2nifti.

Prepare Fieldmap

prepare_fieldmap is a command line tool for converting scanner saved fieldmap to units of radians/sec. As of now it only works with fieldmap saved with Siemens sequence 'gre_field_mapping'.

Download Links: Windows 64 bit (Author: Chitresh Bhushan, Last Modified: August 12, 2013)

• Requires MATLAB compiler runtime (v2012a).

prepare_fieldmap can be run from command line using following syntax:

NIfTI input:

prepare_fieldmap.exe --out=<output_filename> [options] --in=<scanner_saved_fieldmap>

Dicom input:

prepare_fieldmap.exe --out=<output_filename> [options] -d <dicom_dir 1>..<dicom_dir N>

where, <scanner_saved_fieldmap is the input filename of scanner saved fieldmap in NIfTI format (.nii or .nii.gz), <output_filename> is the output filename. [options] is optional input defined below. <dicom_dir 1>,..,<dicom_dir N> is the path to dicoms saved by scanner. These dicoms paths should contain only dicom files for fieldmap sequence. In case dicom input is not working as expected, please first convert dicom image to nifti format using some external converter and use nifti input as shown above.

Optional Arguments:

--ref-vol=<reference_volume>

where, <reference_volume> is filename of reference volume NIfTI format (.nii or .nii.gz) which can be used to estimate or define a mask of the head. This mask is used to replace noisy fieldmap estimate outside the head by extrapolating the fieldmap. The reference volume can be the 3D/4D magnitude image used for fieldmap estimation (and as saved by the scanner) OR it can be a manually drawn mask. In the former case, prepare_fieldmap will estimate the head mask from the reference volume based on instensity. The Estimated mask is also saved to disk with file name as <output_filename>.mask.nii.gz. In case the automatic estimated mask is not accurate, please refine the mask manually in BrainSuite and re-run with refined mask as reference volume.