Simulated MRI images and reference fiber tracts of 99 subjects

This archive contains simulated MRI images (T1, T2, dMRI) of 99 healthy subjects as well as corresponding reference fiber tracts used for the MRI simulation. The archive is primarily intended for the training and validation of fiber tractography methods but is well suited for many other tasks in the area o diffusion-weighted MRI image processing. The simulation was performed using the Fiberfox1 dMRI simulation tool included in MITK Diffusion2,3. Fiberfox uses reference fiber tracts, generated using TractSeg4,5 and MITK Diffusion, and volume fraction maps, generated using MRtrix6 and FSL7,8, as input to simulate the actual k-space acquisition. This enables highly realistic looking image contrasts and artifacts such as (inter volume) head motion, spikes, eddy currents, ghosts, Gibbs ringing, inhomogeneity induced distortions, signal drift and complex gaussian noise. The reference data was created on the basis of 99 unrelated subjects from the HCP9 young adult dataset10. The simulation parameters including tissue properties, such as T1/T2 relaxation times and diffusivities, as well as scanner parameters, such as TE and TR, were automatically optimized using Optunity11 to create realistic image contrasts. Logging of the complete simulation process to ensure reproducibility was performed using CmdInterface12. This data archive only contains the simulated MRI images and the corresponding reference tracts. Additional data such as the volume fraction maps, simulation parameters, detailed logfiles and additional simulation outputs are not included but might be published at a later timepoint. If you are using this dataset in your work, please cite "Neher et al. Fiberfox: facilitating the creation of realistic white matter software phantoms. Magn Reson Med. 2014 Nov;72(5):1460–1470." as well as the reference of the dataset itself and include the link to MITK Diffusion. References and links: 1. Neher et al. “Fiberfox: Facilitating the Creation of Realistic White Matter Software Phantoms.” Magnetic Resonance in Medicine 72, no. 5 (November 2014): 1460–70. 2. MITK Diffusion, https://github.com/MIC-DKFZ/MITK-Diffusion 3. Nolden et al. “The Medical Imaging Interaction Toolkit: Challenges and Advances : 10 Years of Open-Source Development.” International Journal of Computer Assisted Radiology and Surgery 8, no. 4 (July 2013): 607–20. 4. TractSeg, https://github.com/MIC-DKFZ/TractSeg/ 5. Wasserthal et al. “TractSeg - Fast and Accurate White Matter Tract Segmentation.” NeuroImage 183 (August 4, 2018): 239–53. 6. MRtrix 5ttgen, https://mrtrix.readthedocs.io/en/3.0_rc3/reference/scripts/5ttgen.html 7. FSL, https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/ 8. Jenkinson et al. “FSL.” Neuroimage 62 (2012): 782–790. 9. Van Essen et al. (2013). The WU-Minn Human Connectome Project: An overview. NeuroImage 80(2013):62-79. 10. HCP young adult dataset, https://db.humanconnectome.org/data/projects/HCP_1200 11. Optunity, https://optunity.readthedocs.io/en/latest/ 12. CmdInterface command line and python experiment logging, https://github.com/MIC-DKFZ/cmdint