Peter Neher1 and Klaus Maier-Hein1,2,3
1Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Medical Faculty, University of Heidelberg, Heidelberg, Germany, 3Pattern Analysis and Learning Group, Heidelberg University Hospital, Heidelberg, Germany
1Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany, 2Medical Faculty, University of Heidelberg, Heidelberg, Germany, 3Pattern Analysis and Learning Group, Heidelberg University Hospital, Heidelberg, Germany
We present the openly available 99 simulated brains dataset containing artificial MR images and reference fiber tracts suitable for tractography evaluation as well as training of machine-learning based dMRI processing approaches.
Illustration of simulated MR images with various animated artifacts (a bit
excessive for illustration purposes): eddy current distortions (a), intensity drift (b), head motion and spike (c), head motion, eddy currents and noise (d), Gibbs ringing (e), inhomogeneity distortions (f).
Comparison between the B0 image contrast of a simulated (a) and the corresponding real reference image (b). This figure illustrates that using the automatic parameter optimization it was possible to closely approximate the contrasts of a real image.
