Xu Yao1,2, Chengjian Qiu1, Yuqing Song1, Zhe Liu1,*
Intelligent Automation & Soft Computing, Vol.37, No.3, pp. 2583-2594, 2023, DOI:10.32604/iasc.2023.037205
Abstract As the pancreas only occupies a small region in the whole abdominal computed tomography (CT) scans and has high variability in shape, location and size, deep neural networks in automatic pancreas segmentation task can be easily confused by the complex and variable background. To alleviate these issues, this paper proposes a novel pancreas segmentation optimization based on the coarse-to-fine structure, in which the coarse stage is responsible for increasing the proportion of the target region in the input image through the minimum bounding box, and the fine is for improving the accuracy of pancreas segmentation by enhancing the data diversity… More >
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