QC-Automator: Deep Learning-Based Automated Quality Control for Diffusion MR Images

@article{Samani2019QCAutomatorDL,
  title={QC-Automator: Deep Learning-Based Automated Quality Control for Diffusion MR Images},
  author={Zahra Riahi Samani and Jacob A. Alappatt and Drew Parker and Abdol Aziz Ould Ismail and Ragini Verma},
  journal={Frontiers in Neuroscience},
  year={2019},
  volume={13}
}
Quality assessment of diffusion MRI (dMRI) data is essential prior to any analysis, so that appropriate pre-processing can be used to improve data quality and ensure that the presence of MRI artifacts do not affect the results of subsequent image analysis. Manual quality assessment of the data is subjective, possibly error-prone, and infeasible, especially considering the growing number of consortium-like studies, underlining the need for automation of the process. In this paper, we have… 

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