The ISMRM 2015 Tractography Challenge


Data generation

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  1. White matter bundles were manually segmentated from a HCP subject’s tractogram based on definitions found in Diffusion Tensor Imaging, Introduction and Atlas, which was written by challenge coorganizers Bram Stieltjes and Klaus Maier-Hein, as well as R.M. Brunner and F.B. Laun.

  2. The ISMRM 2015 Tractography challenge was based on an artificial phantom generated using the Fiberfox, based on these 25 manually segmented bundles, which serve as ground truth models. They are used as artificial fibers to generate the raw diffusion MRI dataset, as described in the Fiberfox paper by Neher et al. Hence, this is just another way to generate a phantom dataset based on realistic looking streamline fibers. The aim was to create a realistic, clinical-style dataset that provided challenging bundles configurations.

Data description

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The clinical-style challenge dataset consists of a 2mm isotropic diffusion acquisition, with 32 gradient directions, b-value=1000 s/mm2. It also contains one b=0 image and an optional b=0 volume, with reversed phase-encoding direction. Additionnaly, a T1-like image is provided.

From left to right: DWI, fieldmap and T1.

Acquisition parameters

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The diffusion acquisition was simulated with the following parameters:

  • Phase direction: Y
  • No acceleration factor
  • No partial Fourier
  • TE = 108ms
  • Dwell time = 1ms

** Important note about the Field Map: Please note that the same fieldmap is applied to all image volumes, regardless of head motion. This is a limitation of the current generation technique. In reality, the fieldmap should move with the head, but this is currently not the case in the simulated dataset.


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All datasets refer to the same “subject”. All files necessary to run the standalone scoring script – config file, masks of the bundles (along with the ground-truth bundles) – are available in the Tools tab.

  • Basic dataset.

    • Updated on 2015-03-06.
    • Changes: new readme file. Contains the DWI, the field map, the T1 image and the gradients information.
    • md5: 6ab9c875709e73ab394a09aac66356ff
  • Dataset with additional, reversed-phase b=0.

    • Added on 2015-04-01.
    • Contains the same datasets as the basic dataset, with an additional B=0 image, with the reversed phase-encoding direction.
    • md5: a08671a9e302d84af18bd391d70cb671
  • Ground truth bundles: VTK format.

    • The 25 basic ground truth bundles.
    • IMPORTANT NOTE: Data format managing was not very well defined in 2015. A lot of effort was made to ensure that data would be readable by any software. Yet, things have evolved. As of 08.2022, the standalone tool has been updated. The code is now in python3, and tractograms are loaded through Dipy’s Stateful Tractogram tools. Previous version of the code applied authomatic 0.5 shifts when loading files as trk, this is NOT done anymore. We have removed the .tck and .trk versions. Please use the safer .fib version (VTK files). These files are easily loadable through Dipy / Scilpy, the two libraries we use.
    • md5: d5696ef555d669c1cfd341c0713c6ff4.
  • Ground truth, artifact-free DWI.

    • The ground truth Diffusion Weighted Image, without any artifact. Includes the gradients information.
    • Was updated on 2015-07-20.
    • md5: 2bfc6b19136f10e8ee10079fa0c53274
  • Files used to generate Ground Truth DWI.

    • The files of this archive can be used with Fiberfox to generate the ground truth DWI datasets. See included Readme file for more information.
    • Was added on 2015-07-20.
    • md5: c7c874a28dc24773afcbc5afa6293257
  • The ground truth data needed to score your own tractogram is available in the Tools table .

Archive integrity verification

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You can check the integrity of your download by computing the MD5 checksum of the downloaded archive. Instructions on how to do so:

The value you should get for each download is written after the download link, in the Downloads section.