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The contrast-enhanced MRI can be substituted by unenhanced MRI in identifying and automatically segmenting primary nasopharyngeal carcinoma with the aid of deep learning models: An exploratory study in large-scale population of endemic area.
Deng, Yishu; Li, Chaofeng; Lv, Xing; Xia, Weixiong; Shen, Lujun; Jing, Bingzhong; Li, Bin; Guo, Xiang; Sun, Ying; Xie, Chuanmiao; Ke, Liangru.
Affiliation
  • Deng Y; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Ce
  • Li C; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Ce
  • Lv X; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen Univers
  • Xia W; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen Univers
  • Shen L; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Minimally Invasive Therapy, Sun Yat-Sen Unive
  • Jing B; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Ce
  • Li B; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Information, Sun Yat-Sen University Cancer Ce
  • Guo X; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Nasopharyngeal Carcinoma, Sun Yat-Sen Univers
  • Sun Y; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Radiation Oncology, Sun Yat-Sen University Ca
  • Xie C; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Radiology, Sun Yat-Sen University Cancer Cent
  • Ke L; State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Guangzhou 510060, China; Department of Radiology, Sun Yat-Sen University Cancer Cent
Comput Methods Programs Biomed ; 217: 106702, 2022 Apr.
Article in En | MEDLINE | ID: mdl-35228147
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nasopharyngeal Neoplasms / Deep Learning Type of study: Observational_studies Limits: Humans Language: En Journal: Comput Methods Programs Biomed Journal subject: INFORMATICA MEDICA Year: 2022 Type: Article
Fulltext
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PubMed Links
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Nasopharyngeal Neoplasms / Deep Learning Type of study: Observational_studies Limits: Humans Language: En Journal: Comput Methods Programs Biomed Journal subject: INFORMATICA MEDICA Year: 2022 Type: Article