MITK Diffusion Imaging (MITK-DI)

Table of Contents

• Components
  • Data Import
  • Preprocessing and Reconstruction
  • Fiber Tracking
  • Quantification
  • Connectomics
• Known Issues
• Technical Information for Developers
• References

This module provides means to diffusion weighted image reconstruction, visualization and quantification. Diffusion tensors as well as different q-ball reconstruction schemes are supported. Q-ball imaging aims at recovering more detailed information about the orientations of fibers from diffusion MRI measurements and, in particular, to resolve the orientations of crossing fibers.

Components

MITK Diffusion consists of further components, which have their own documentation, see:

Data Import

• Importing Data

Preprocessing and Reconstruction

Register or denoise original data and convert it into tensor or q-ball images.

• DWI Registration
• Preprocessing of Diffusion Images
• Signal Modeling
• ODF Visualization
• ODF Details
• ODF Peak Extraction
• DWI Denoising

Fiber Tracking

Create and work with fiber tractographies.

• Fiber Processing
• Global Gibbs Tractography
• Machine Learning Based Streamline Tractography
• Probabilistic Streamline Tractography
• Fiber Processing
• Fiber Quantification
• Deterministic Streamline Tractography
• Fiberfox DW-MRI Simulation
• Fieldmap Generator

Quantification

Create parameter maps and quantify different properties.

• Scalar Indices
• Intra-voxel incoherent motion estimation (IVIM)
• Partial Volume Analysis
• The TBSS View

Connectomics

Create and analyse connectome networks.

• The Connectomics Perspective

Known Issues

• Dicom Import: The dicom import has so far only been implemented for Siemens dicom images. MITK-DI is capable of reading the nrrd format, which is documented elsewhere [1, 2]. These files can be created by combining the raw image data with a corresponding textual header file. The file extension should be changed from *.nrrd to *.dwi or from *.nhdr to *.hdwi respectively in order to let MITK-DI recognize the diffusion related header information provided in the files.

Technical Information for Developers

The diffusion imaging module uses additional properties beside the ones in use in other modules, for further information see The Diffusion Imaging Properties .

References

Further reading regarding diffusion:

1. http://teem.sourceforge.net/nrrd/format.html
2. http://www.cmake.org/Wiki/Getting_Started_with_the_NRRD_Format
3. C.F.Westin, S.E.Maier, H.Mamata, A.Nabavi, F.A.Jolesz, R.Kikinis, "Processing and visualization for Diffusion tensor MRI", Medical image Analysis, 2002, pp 93-108
4. Tuch, D.S., 2004. Q-ball imaging. Magn Reson Med 52, 1358-1372.
5. Descoteaux, M., Angelino, E., Fitzgibbons, S., Deriche, R., 2007. Regularized, fast, and robust analytical Q-ball imaging. Magn Reson Med 58, 497-510.
6. Aganj, I., Lenglet, C., Sapiro, G., 2009. ODF reconstruction in q-ball imaging with solid angle consideration. Proceedings of the Sixth IEEE International Symposium on Biomedical Imaging Boston, MA.
7. Goh, A., Lenglet, C., Thompson, P.M., Vidal, R., 2009. Estimating Orientation Distribution Functions with Probability Density Constraints and Spatial Regularity. Med Image Comput Comput Assist Interv Int Conf Med Image Comput Comput Assist Interv LNCS 5761, 877 ff.
8. J.-D. Tournier, S. Mori, A. Leemans., 2011. Diffusion Tensor Imaging and Beyond. Magn Reson Med 65, 1532-1556.