Data set for sub-millimetre MRI tissue class segmentation

<p>Sub-millimetre 7Tesla MRI image data set of the human brain for supervised training of algorithms to perform tissue class segmentation.</p> <p>The dataset contains preprocessed MRI images (co-registered + bias corrected) and corresponding ground truth labels.</p> <p>The dataset contains two different acquisitions:</p> <p>- MPRAGE dataset, based on 5 subjects, with T1w, PDw and T2w images</p> <p>- MP2RAGE dataset, based on 4 subjects, with inv1, inv2 and me gre images</p> <p>&nbsp;</p> <p>The following ground truth labels are provided:<br> [1] white matter<br> [2] grey matter<br> [3] cerebrospinal fluid<br> [4] ventricles<br> [5] subcortical<br> [6] vessels<br> [7] sagittal sinus</p> <p>Images are saved as nifti files and organized in BIDS format.</p> <p>This dataset is an extension of the following, initial dataset publication:</p> <p>* Dataset: A scalable method to improve gray matter segmentation at ultra high field MRI.</p> <p>The initial dataset is also available as a zenodo repository and can be downloaded from:<br> https://zenodo.org/record/1206163</p>