Joint dense residual and recurrent attention network for dce-mri breast tumor segmentation

HIGHLIGHTS

• who: ChuanBo Qin and colleagues from the Faculty of Intelligent Manufacturing, Wuyi University, Jiangmen, China have published the research: Joint Dense Residual and Recurrent Attention Network for DCE-MRI Breast Tumor Segmentation, in the Journal: Computational Intelligence and Neuroscience of 20/04/2022
• what: The authors propose an automatic and accurate two-stage U-Net-based segmentation framework for breast tumor detection using dynamic contrast-enhanced MRI (DCE-MRI). In this regard, the authors propose a dense residual module and recurrent attention mechanism, which can further improve the segmentation performance of U-Net-based approaches . . .
  

   

  

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