{"title":"基于灰度均值与标准差比的CT脑扫描图像窗宽设置估计","authors":"C. S. Ee, K. Sim, V. Teh, F. F. Ting","doi":"10.1109/ICORAS.2016.7872600","DOIUrl":null,"url":null,"abstract":"Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.","PeriodicalId":393534,"journal":{"name":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio\",\"authors\":\"C. S. Ee, K. Sim, V. Teh, F. F. Ting\",\"doi\":\"10.1109/ICORAS.2016.7872600\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.\",\"PeriodicalId\":393534,\"journal\":{\"name\":\"2016 International Conference on Robotics, Automation and Sciences (ICORAS)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Robotics, Automation and Sciences (ICORAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICORAS.2016.7872600\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Robotics, Automation and Sciences (ICORAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICORAS.2016.7872600","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Estimation of window width setting for CT scan brain images using mean of greyscale level to standard deviation ratio
Computed tomography (CT) is the initial imaging modality for stroke diagnoses. However, efficient approach to estimate window setting for CT brain images is not yet founded. Window setting consists of 2 components: window center (WC) and window width (WW). In this paper, a novelty estimation method namely estimation of window width using mean of greyscale level to standard deviation ratio (EWWMGSR) is developed to determine the WW for CT brain images, with WC is fixed as 40 HU. The results show the robustness of EWWMGSR method in determining the estimated WW value, compared with prior existing approaches. Most of them are determined manually and within a very small range. EWWMGSR estimates better window width value for radiologists in CT brain image diagnoses.