• Corpus ID: 220936203

Automated Segmentation of Brain Gray Matter Nuclei on Quantitative Susceptibility Mapping Using Deep Convolutional Neural Network

@article{Chai2020AutomatedSO,
  title={Automated Segmentation of Brain Gray Matter Nuclei on Quantitative Susceptibility Mapping Using Deep Convolutional Neural Network},
  author={Chao Chai and Pengchong Qiao and Bin Zhao and Huiying Wang and Guohua Liu and Hong Wu and Ewart Mark Haacke and Wen Shen and Chen Cao and Xinchen Ye and Zhiyang Liu and Shuang Xia},
  journal={ArXiv},
  year={2020},
  volume={abs/2008.00901}
}
Abnormal iron accumulation in the brain subcortical nuclei has been reported to be correlated to various neurodegenerative diseases, which can be measured through the magnetic susceptibility from the quantitative susceptibility mapping (QSM). To quantitively measure the magnetic susceptibility, the nuclei should be accurately segmented, which is a tedious task for clinicians. In this paper, we proposed a double-branch residual-structured U-Net (DB-ResUNet) based on 3D convolutional neural… 

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