Nasopharyngeal carcinoma (NPC) is one of the most common malignant tumours of the head and neck, and improving the efficiency of its diagnosis and treatment strategies is an important goal. With the development of the combination of artificial intelligence (AI) technology and medical imaging in recent years, an increasing number of studies have been conducted on image analysis of NPC using AI tools, especially radiomics and artificial neural network methods. In this review, we present a comprehensive overview of NPC imaging research based on radiomics and deep learning. These studies depict a promising prospect for the diagnosis and treatment of NPC. The deficiencies of the current studies and the potential of radiomics and deep learning for NPC imaging are discussed. We conclude that future research should establish a large-scale labelled dataset of NPC images and that studies focused on screening for NPC using AI are necessary.
第一作者单位:[1]Wuhan Univ, Renmin Hosp, Dept Otolaryngol Head & Neck Surg, 238 Jie Fang Rd, Wuhan 430060, Peoples R China
通讯作者:
推荐引用方式(GB/T 7714):
Li Song,Deng Yu-Qin,Zhu Zhi-Ling,et al.A Comprehensive Review on Radiomics and Deep Learning for Nasopharyngeal Carcinoma Imaging[J].DIAGNOSTICS.2021,11(9):doi:10.3390/diagnostics11091523.
APA:
Li, Song,Deng, Yu-Qin,Zhu, Zhi-Ling,Hua, Hong-Li&Tao, Ze-Zhang.(2021).A Comprehensive Review on Radiomics and Deep Learning for Nasopharyngeal Carcinoma Imaging.DIAGNOSTICS,11,(9)
MLA:
Li, Song,et al."A Comprehensive Review on Radiomics and Deep Learning for Nasopharyngeal Carcinoma Imaging".DIAGNOSTICS 11..9(2021)