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 time and the
limitation of… More >
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