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The TORTOISE website has been moved to https://tortoise.nibib.nih.gov.

For any information about TORTOISE generation V3.x.x, please refer to the new website.

DIFF_CALC

If you use our software in your research, the algorithms listed below have been published elsewhere. Downloadable pdf copies of the articles are available by clicking the download links. Please cite the appropriate references in yourwork. A general reference for TORTOISE is shown below.1

DIFF_CALC is a software package for the estimation of the diffusion tensor in each voxel and for the computation of tensor-derived quantities. Functions include:

  1. Automated2,14 and manual (ROI based) image noise estimation
  2. Tensor computation approaches including weighted and unweighted linear, non-linear3, and robust fitting including RESTORE5 and informed RESTORE14
  3. Future support of dual compartment6, and Newton constrained fitting7
  4. Proper weighting in the tensor fitting to account for changes in the statistical properties of the image due to interpolation from image registration8,9
  5. Goodness of fit analysis with display of the residuals of the fitting
  6. Tensor derived quantities in analyze and nifti formats including Trace(D), eignevalues, eigenvectors, fractional anisotropy, relative anisotropy, volume ratio10, lattice index11, directionally encoded color (DEC) maps12, Westin's measures13, skewness1, linefield representation of principal eigenvector, etc.
  7. ROI analysis including orthogonal viewer for 3D Volume of Interest (VOI) analysis
  8. Export modules for diffusion weighted images and/or diffusion tensor to: FSL, Camino, TrackVis, Slicer, DTI-TK, NRRD, VTK, DTI Studio

Access to the Software Guide

Access a list of the outputs of the tensor fitting Version 3.2.10

For frequently asked questions, please visit our FAQ.

References

  1. C. Pierpaoli, L. Walker, M. O. Irfanoglu, A. Barnett, P. Basser, L-C. Chang, C. Koay, S. Pajevic, G. Rohde, J. Sarlls, and M. Wu, 2010, TORTOISE: an integrated software package for processing of diffusion MRI data, ISMRM 18th Annual Meeting, Stockholm, Sweden, #1597.
  2. Koay CG, Özarslan E and Basser PJ. A signal transformational framework for breaking the noise floor and its applications in MRI. J Magn Reson 2009; 197: 108-119.
  3. Basser, P.J., Mattiello, J., and LeBihan, D. (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J Magn Reson B 103:247-254.
  4. Mangin JF, Poupon C, Clark C, Le Bihan D, Bloch I. (2002) Distortion correction and robust tensor estimation for MR diffusion imaging. Med Image Anal. 6(3):191-8.
  5. Chang, L.C., Jones, D.K., and Pierpaoli, C. (2005) RESTORE: Robust estimation of tensors by outlier rejection. Magn Reson Med. 53:1088-1095.
  6. Kim, S., et al. (2005) Dependence on diffusion time of apparent diffusion tensor of ex vivo calf tongue and heart. 13th Annual ISMRM, Miami Beach, Florida, USA, #1285
  7. Koay, C.G., Chang, L-C., Carew, J.D., Pierpaoli, C., and Basser, P.J. (2006) A unifying theoretical and algorithmic framework for least squares methods of estimation in diffusion tensor imaging. J Magn Reson. 182:115-125.
  8. Rohde, G.K., Barnett, A.S., Basser, P.J., and Pierpaoli, C. (2005) Estimating intensity variance due to noise in registered images: Applications to diffusion tensor MRI. Neuroimage 26:673-684.
  9. Irfanoglu, M. O., Walker, L., Machiraju, R., Pierpaoli, C. (2011). Accounting for changes in signal variance in diffusion weighted images following interpolation for motion and distortion correction. ISMRM 19th Annual Meeting and Exhibition, Montreal, Canada. PDF
  10. Basser, P.J. and Pierpaoli, C. (1996) Microstructural and physiological features of tissues elucidated by quantitative-diffusion-tensor MRI. J Magn Reson B. 111:209-219.
  11. Pierpaoli, C. and Basser, P.J. (1996) Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med. 36:893-906.
  12. Pajevic, S. and Pierpaoli, C. (1999) Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data: application to white matter fiber tract mapping in the human brain. Magn Reson Med. 42:526-540.
  13. Peled S, Gudbjartsson H, Westin CF, Kikinis R, Jolesz FA. (1998) Magnetic resonance imaging shows orientation and asymmetry of white matter fiber tracts. Brain Res. 5;780(1):27-33.
  14. Chang, L.C., Walker, L., Pierpaoli, C., (2012) Informed RESTORE: A Method for Robust Estimation of Diffusion Tensor from Low Redundancy Datasets in the Presence of Physiological Noise Artifacts. Magn Reson Med. 68(5):1654-63.