filip-szczepankiewicz/Szczepankiewicz_DIB_2019

Szczepankiewicz et al. DIB 2019, open source data acquired with tensor-valued diffusion MRI.

Linear, planar and spherical tensor-valued diffusion MRI data by free waveform encoding in healthy brain, water, oil and liquid crystals

Filip Szczepankiewicz*, Scott Hoge, Carl-Fredrik Westin

Radiology, Brigham and Women’s Hospital, Boston, MA, US
Harvard Medical School, Boston, MA, US

*Corresponding author:
Filip Szczepankiewicz (filip.szczepankiewicz@med.lu.se)

Overview

This is an open source repository that supplies diffusion-MRI data with tensor-valued diffusion encoding. Data is available in a healthy human brain in vivo as well as water, oil and liquid crystal phantoms. The repository also contains detailed information and resources concerning the experiment and its design.

Value of the data:

• The data facilities design and testing of analysis techniques that require tensor-valued (or multidimensional) diffusion encoding. This provides value since acquisition of such data currently relies on a custom pulse sequence that is not widely available.
• The data includes repeated sampling of spherical b-tensors for analysis of noise characteristics.
• A subset of the data is matched with respect to the diffusion time spectrum for analysis of models of diffusion time dependency.

Download specific data packages

GitHub does not have straightforward support for downloading of individual folders. Therefore, the following links (powered by DownGit) enable download of specific folders.

• Brain
  • DICOM
  • NII (mddMRI format)
  • NII (standard)
  • NII (Boito Subsamples)
• Hex
  • DICOM
  • NII (mddMRI format)
  • NII (standard)
• Oil
  • DICOM
  • NII (mddMRI format)
  • NII (standard)
• Water
  • DICOM
  • NII (mddMRI format)
  • NII (standard)

Example of analysis pipeline

• A brief example of how to calculate QTI parameters from data (based on the merged MD-MRI fromat) can be found in the examples folder.
• A throrough, step-by-step example of how to use the data in the Multidimensional Diffusion MRI framework, including motion correction, parameter fitting, and registration with anatomical sequences, can be found here.

Reference and details

If this resource was useful for you, please cite the Data in Brief paper connected to this project:
F Szczepankiewicz, S Hoge, C-F Westin. Linear, planar and spherical tensor-valued diffusion MRI data by free waveform encoding in healthy brain, water, oil and liquid crystals. Data in Brief (2019), DOI: https://doi.org/10.1016/j.dib.2019.104208

Related resources can be found at the FWF sequence GIT repository