Cyclotron Research Centre
Attribution Share Alike
Yes
University of Liège
NITRC
High-quality diffusion-weighted imaging of Parkinson's disease
Python
Christophe Phillips
This project contains data and analysis pipelines for a set of 53 subjects in a cross-sectional Parkinson's disease (PD) study. The dataset contains diffusion-weighted images (DWI) of 27 PD patients and 26 age, sex, and education-matched control subjects. The DWIs were acquired with 120 unique gradient directions, b=1000 and b=2500 s/mm2, and isotropic 2.4 mm3 voxels. The acquisition used a twice-refocused spin echo sequence in order to avoid distortions induced by eddy currents.
Processing scripts for the paper can be found on Github: https://github.com/CyclotronResearchCentre/parktdi_scripts
2014-9-23
Demographic data
2014-6-18
Motion-corrected diffusion-weighted images
2014-6-18
Normalized TDI Maps
High-quality diffusion-weighted imaging of Parkinson's disease
Data, Parkinson Disease, Clinical Neuroinformatics, MR, Attribution Share Alike, English, NiPyPe, Python, NIfTI-1
http://www.nitrc.org/projects/parktdi/, http://www.nitrc.org/projects/parktdi/
c.phillips@ulg.ac.be