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SAR-U-Net: squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography [article]

Jinke Wang, Peiqing Lv, Haiying Wang, Changfa Shi
2021 arXiv   pre-print
and objective: In this paper, a modified U-Net based framework is presented, which leverages techniques from Squeeze-and-Excitation (SE) block, Atrous Spatial Pyramid Pooling (ASPP) and residual learning  ...  for accurate and robust liver CT segmentation, and the effectiveness of the proposed method was tested on two public datasets LiTS17 and SLiver07.  ...  The U-Net based framework leverages the advantages of Squeeze-and-Excitation, Atrous Spatial Pyramid Pooling, and residual learning techniques.  ... 
arXiv:2103.06419v3 fatcat:c3stk3hsfjarfa2vrioti5nqpm