A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images

@article{Xue2020AM2,
  title={A multi-path 2.5 dimensional convolutional neural network system for segmenting stroke lesions in brain MRI images},
  author={Yunzhe Xue and Fadi G. Farhat and Olga Boukrina and Anna M. Barrett and Jeffrey R. Binder and Usman Roshan and William W. Graves},
  journal={NeuroImage : Clinical},
  year={2020},
  volume={25}
}
Automatic identification of brain lesions from magnetic resonance imaging (MRI) scans of stroke survivors would be a useful aid in patient diagnosis and treatment planning. [...] Key Method Our system has nine end-to-end UNets that take as input 2-dimensional (2D) slices and examines all three planes with three different normalizations. Outputs from these nine total paths are concatenated into a 3D volume that is then passed to a 3D convolutional neural network to output a final lesion mask. We trained and…Expand
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