High Angular Resolution Diffusion Imaging (HARDI) Tools

Authors: Erick J. Canales-Rodrí­guez, Lester Melie-Garcí­a, Yasser Iturria-Medina, Yasser Alemán-Gómez

Date: 2011, Version: 1.0

Description

This is a collection of MATLAB routines for the analysis of High Angular Resolution Diffusion Imaging (HARDI) data. It is a subset of the code internally used in the unit of research at the Benito Menni Hospital (Barcelona, Spain), the Cuban Neuroscience Center (Havana, Cuba), and the Medical Imaging Laboratory at Gregorio Marañón Hospital (Madrid, Spain).

List of reconstruction methods currently included:

1. Q-Ball Imaging (QBI)
2. Mono-Exponential-Exact Q-Ball Imaging (MeEQBI)
3. Diffusion Orientation Transform (DOT)
4. Revisited version of the DOT method (DOTR1 and DOTR2)

All the reconstructions are based on real-valued spherical harmonics expansions. Some useful free functions provided in the Bioelectromagnetism Matlab Toolbox for tessellating spheres are also included. The codes illustrate the use and performance of the above listed methods in simulated data, generated from a multi-tensor diffusion model for a single voxel under experimental noise (Rician). To use the above methods in real data it is mandatory to convert the raw images (DICOM/ANALYZE) to matlab matrix format .mat (using for example SPM software ) and then compute the implemented algorithms for each voxel in the brain-image.

Download the software

Do not hesitate to use them for your own research and to contact the authors: ejcanalesr@gmail.com

Examples of usage

Firstly you need to add the main folder and all it's subdirectories to the Matlab path. Then run any of the following test scripts (click on the above items to view the html files generated from these codes):

• test_QBI_example.m
• test_MeEQBI_example.m
• test_DOT_example.m
• test_DOTR1_example.m
• test_DOTR2_example.m

References

1. David S. Tuch, Reese TG, Wiegell MR, et al (2002). "High angular resolution diffusion imaging reveals intravoxel white matter fiber heterogeneity". Magn. Res. Med. 48 (4): 577-582.
2. David S. Tuch. Q-ball imaging. Magn. Reson. Med., 52(6):1358-1372, 2004.
3. Maxime Descoteaux, Elaine Angelino, Shaun Fitzgibbons, and Rachid Deriche. Regularized, Fast and Robust Analytical Q-Ball Imaging. Magn. Reson. Med., 58:497-510, 2007.
4. Evren Özarslan, Timothy M. Shepherd, Baba C. Vemuri, Stephen J. Blackband, and Thomas H. Mareci. Resolution of complex tissue microarchitecture using the diffusion orientation transform (DOT). NeuroImage, 36(3):1086-1103, 2006.
5. Maxime Descoteaux, Elaine Angelino, Shaun Fitzgibbons, and Rachid Deriche. Apparent diffusion coefficients from high angular resolution diffusion imaging: Estimation and applications. Magn. Reson. Med., 56(2):395-410, 2006.
6. Adam W. Anderson. Measurement of Fiber Orientation Distributions Using High Angular Resolution Diffusion Imaging. Magn. Reson. Med.,54 (5):1194-1206, 2005.
7. Erick J. Canales-Rodrí­guez, Lin CP, Iturria-Medina Y, Yeh CH, Cho KH, Melie-Garcí­a L. Diffusion orientation transform revisited. Neuroimage, 2010, Vol 49, 2, 1326-1339.
8. Erick J. Canales-Rodríguez, Lester Melie-Garcí­a, and Yasser Iturria-Medina. Mathematical Description of q-Space in Spherical Coordinates: Exact q-Ball Imaging. Magnetic Resonance in Medicine, 2009, Vol 61, 3, 1350-1367.
9. Lester Melie-Garcí­a, Erick J. Canales-Rodríguez, Yasser Alemán-Gómez, Ching-Po Lin, Yasser Iturria-Medina, and Pedro Valdés-Hernández.A Bayesian framework to identify principal intravoxel diffusion profiles based on Diffusion-Weighted MR Imaging. Neuroimage, 2008, Vol 42, 2, 750-770.