Assessing the Accuracy and Reproducibility of PARIETAL: A Deep Learning Brain Extraction Algorithm.

Journal: Journal of magnetic resonance imaging : JMRI
Published Date: Jun 16, 2021

Abstract

BACKGROUND: Manual brain extraction from magnetic resonance (MR) images is time-consuming and prone to intra- and inter-rater variability. Several automated approaches have been developed to alleviate these constraints, including deep learning pipelines. However, these methods tend to reduce their performance in unseen magnetic resonance imaging (MRI) scanner vendors and different imaging protocols.

Authors

  • Sergi Valverde
    Research institute of Computer Vision and Robotics, University of Girona, Spain. Electronic address: svalverde@eia.udg.edu.
  • Llucia Coll
    Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain.
  • Liliana Valencia
    Research Institute of Computer Vision and Robotics, University of Girona, Girona, Spain.
  • Albert Clèrigues
    Institute of Computer Vision and Robotics, University of Girona, Spain. Electronic address: albert.clerigues@udg.edu.
  • Arnau Oliver
    Research institute of Computer Vision and Robotics, University of Girona, Spain.
  • Joan C Vilanova
    Girona Magnetic Resonance Center, Spain.
  • Lluís Ramió-Torrentà
    Multiple Sclerosis and Neuroimmunology Unit, Dr. Josep Trueta University Hospital, Spain.
  • Àlex Rovira
    Magnetic Resonance Unit, Dept of Radiology, Vall d'Hebron University Hospital, Spain.
  • Xavier Lladó
    Research institute of Computer Vision and Robotics, University of Girona, Spain.

Keywords

External Resources

Popular Topics
Recent Journals