A transformer-based generative adversarial network for brain tumor segmentation

HIGHLIGHTS

• who: Senchun Chai from the University, China have published the paper: A transformer-based generative adversarial network for brain tumor segmentation, in the Journal: (JOURNAL)
• what: The authors focus on the segmentation of brain tumors with the help of magnetic_resonance imaging (MRI) consisting of multi-modality scans. Inspired by some attempts (Wang W. et_al, 2021; Hatamizadeh et_al, 2022) of fusing transformer with 3D CNNs, the authors design an encoder-decoder generator with deep supervision, where both encoder and decoder are 3D CNNs but the bridge of them is composed of transformer blocks with Resnet. The . . .
  

   

  

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