P. Wangaryattawanich, Jixin Wang, Ginu A. Thomas, A. Chaddad, P. Zinn, R. Colen
{"title":"定量图像特征分析术前GBM患者的生存","authors":"P. Wangaryattawanich, Jixin Wang, Ginu A. Thomas, A. Chaddad, P. Zinn, R. Colen","doi":"10.1109/CoDIT.2014.6996968","DOIUrl":null,"url":null,"abstract":"This paper concerns a preliminary study of the relationship between survival time of both overall and progression free survival, and multiple imaging features of patients with glioblastoma. Simulation results showed that specific imaging features were found to have significant prognostic value to predict survival time in glioblastoma patients.","PeriodicalId":161703,"journal":{"name":"2014 International Conference on Control, Decision and Information Technologies (CoDIT)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Survival analysis of pre-operative GBM patients by using quantitative image features\",\"authors\":\"P. Wangaryattawanich, Jixin Wang, Ginu A. Thomas, A. Chaddad, P. Zinn, R. Colen\",\"doi\":\"10.1109/CoDIT.2014.6996968\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper concerns a preliminary study of the relationship between survival time of both overall and progression free survival, and multiple imaging features of patients with glioblastoma. Simulation results showed that specific imaging features were found to have significant prognostic value to predict survival time in glioblastoma patients.\",\"PeriodicalId\":161703,\"journal\":{\"name\":\"2014 International Conference on Control, Decision and Information Technologies (CoDIT)\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Control, Decision and Information Technologies (CoDIT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CoDIT.2014.6996968\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Control, Decision and Information Technologies (CoDIT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CoDIT.2014.6996968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Survival analysis of pre-operative GBM patients by using quantitative image features
This paper concerns a preliminary study of the relationship between survival time of both overall and progression free survival, and multiple imaging features of patients with glioblastoma. Simulation results showed that specific imaging features were found to have significant prognostic value to predict survival time in glioblastoma patients.