defacing-and-qc-trainingsession

Defacing and QC project: reports of the training session

MRIQC version 23.1.0 derivatives generated from several publicly available datasets ^[1,2,3,4] in the context of the defacing and qc project. Those T1w reports were selected to present a wide range of data quality. In the training session, the raters were asked to independently rate the 20 images and we then discuss their ratings together to ensure that the quality criteria used were interpreted consistently.

How to download this dataset (requires DataLad):

datalad install https://github.com/TheAxonLab/defacing-and-qc-trainingsession.git

When using this dataset please cite:

[1]: Nárai, Ádám, Petra Hermann, Tibor Auer, Péter Kemenczky, János Szalma, István Homolya, Eszter Somogyi, Pál Vakli, Béla Weiss, and Zoltán Vidnyánszky. “Movement-Related Artefacts (MR-ART) Dataset of Matched Motion-Corrupted and Clean Structural MRI Brain Scans.” Scientific Data 9, no. 1 (October 17, 2022): 630. doi:10.1038/s41597-022-01694-8. [2]: Taylor, Paul A., Daniel R. Glen, Richard C. Reynolds, Arshitha Basavaraj, Dustin Moraczewski, and Joset A. Etzel. “Editorial: Demonstrating Quality Control (QC) Procedures in fMRI.” Frontiers in Neuroscience 17 (2023). doi:10.3389/fnins.2023.1205928. [3]: Di Martino, A., C.-G. Yan, Q. Li, E. Denio, F. X. Castellanos, K. Alaerts, J. S. Anderson, et al. “The Autism Brain Imaging Data Exchange: Towards a Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism.” Molecular Psychiatry 19, no. 6 (June 2014): 659–67. doi:10.1038/mp.2013.78. [4]: Gorgolewski, Krzysztof J., Joke Durnez, and Russell A. Poldrack. “Preprocessed Consortium for Neuropsychiatric Phenomics Dataset.” F1000Research, September 22, 2017. doi:10.12688/f1000research.11964.2.