{"title":"红外相机医学图像的时空滤波","authors":"G. Gavriloaia, M. Gavriloaia","doi":"10.1109/TSP.2011.6043705","DOIUrl":null,"url":null,"abstract":"In this paper we proposed an improved method for images filtering with slow time variation obtained from some successive frames of a thermovision camera investigating the heat radiated by human beings. In the first step, a single image is obtained as a result of the mean value evaluation from median filtering of all temporal frames. The standard deviation of each pixel is computed as well. The second stage consisted of a spatial filtering of the image from the first step by using the anisotropic diffusion filtering. New relations for the weighted coefficients of the diffusion matrix were proposed from the local statistic estimators. This method was tested on infrared images of different patients. Both subjective and objective evaluations of a patient image suffering from papillary thyroid cancer showed good performances for improving the signal to noise ratio and location of tumor.","PeriodicalId":341695,"journal":{"name":"2011 34th International Conference on Telecommunications and Signal Processing (TSP)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Spatiotemporal filtering for medical images from an infrared camera\",\"authors\":\"G. Gavriloaia, M. Gavriloaia\",\"doi\":\"10.1109/TSP.2011.6043705\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper we proposed an improved method for images filtering with slow time variation obtained from some successive frames of a thermovision camera investigating the heat radiated by human beings. In the first step, a single image is obtained as a result of the mean value evaluation from median filtering of all temporal frames. The standard deviation of each pixel is computed as well. The second stage consisted of a spatial filtering of the image from the first step by using the anisotropic diffusion filtering. New relations for the weighted coefficients of the diffusion matrix were proposed from the local statistic estimators. This method was tested on infrared images of different patients. Both subjective and objective evaluations of a patient image suffering from papillary thyroid cancer showed good performances for improving the signal to noise ratio and location of tumor.\",\"PeriodicalId\":341695,\"journal\":{\"name\":\"2011 34th International Conference on Telecommunications and Signal Processing (TSP)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 34th International Conference on Telecommunications and Signal Processing (TSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TSP.2011.6043705\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 34th International Conference on Telecommunications and Signal Processing (TSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSP.2011.6043705","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Spatiotemporal filtering for medical images from an infrared camera
In this paper we proposed an improved method for images filtering with slow time variation obtained from some successive frames of a thermovision camera investigating the heat radiated by human beings. In the first step, a single image is obtained as a result of the mean value evaluation from median filtering of all temporal frames. The standard deviation of each pixel is computed as well. The second stage consisted of a spatial filtering of the image from the first step by using the anisotropic diffusion filtering. New relations for the weighted coefficients of the diffusion matrix were proposed from the local statistic estimators. This method was tested on infrared images of different patients. Both subjective and objective evaluations of a patient image suffering from papillary thyroid cancer showed good performances for improving the signal to noise ratio and location of tumor.