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    ARTICLE

    MRI Image Segmentation of Nasopharyngeal Carcinoma Using Multi-Scale Cascaded Fully Convolutional Network

    Yanfen Guo1,2, Zhe Cui1, Xiaojie Li2,*, Jing Peng1,2, Jinrong Hu2, Zhipeng Yang3, Tao Wu2, Imran Mumtaz4

    Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1771-1782, 2022, DOI:10.32604/iasc.2022.019785

    Abstract Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumors of the head and neck, and its incidence is the highest all around the world. Intensive radiotherapy using computer-aided diagnosis is the best technique for the treatment of NPC. The key step of radiotherapy is the delineation of the target areas and organs at risk, that is, tumor images segmentation. We proposed the segmentation method of NPC image based on multi-scale cascaded fully convolutional network. It used cascaded network and multi-scale feature for a coarse-to-fine segmentation to improve the segmentation effect. In coarse segmentation, image blocks and data augmentation… More >

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