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    Tissue Segmentation in Nasopharyngeal CT Images Using TwoStage Learning

    Yong Luo1, Xiaojie Li2, Chao Luo2, Feng Wang1, Xi Wu2, Imran Mumtaz3, Cheng Yi1, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 1771-1780, 2020, DOI:10.32604/cmc.2020.010069

    Abstract Tissue segmentation is a fundamental and important task in nasopharyngeal images analysis. However, it is a challenging task to accurately and quickly segment various tissues in the nasopharynx region due to the small difference in gray value between tissues in the nasopharyngeal image and the complexity of the tissue structure. In this paper, we propose a novel tissue segmentation approach based on a two-stage learning framework and U-Net. In the proposed methodology, the network consists of two segmentation modules. The first module performs rough segmentation and the second module performs accurate segmentation. Considering the training… More >

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