{"title":"一种新的肿瘤分割活动轮廓模型","authors":"Maryam Taghizadeh Dehkordi","doi":"10.1109/PRIA.2017.7983053","DOIUrl":null,"url":null,"abstract":"In this paper, a new energy function has been proposed for tumor segmentation implemented by the level set method. Multi-scale Gaussian filter is applied to the image and its output determines the probability of each pixel belonging to the tumor structure. Introducing the output into the energy function makes the model robust against the inhomogeneous background. Experimental results from MRI verify the desirable performance of the proposed model in comparison with other methods.","PeriodicalId":336066,"journal":{"name":"2017 3rd International Conference on Pattern Recognition and Image Analysis (IPRIA)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"A new active contour model for tumor segmentation\",\"authors\":\"Maryam Taghizadeh Dehkordi\",\"doi\":\"10.1109/PRIA.2017.7983053\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a new energy function has been proposed for tumor segmentation implemented by the level set method. Multi-scale Gaussian filter is applied to the image and its output determines the probability of each pixel belonging to the tumor structure. Introducing the output into the energy function makes the model robust against the inhomogeneous background. Experimental results from MRI verify the desirable performance of the proposed model in comparison with other methods.\",\"PeriodicalId\":336066,\"journal\":{\"name\":\"2017 3rd International Conference on Pattern Recognition and Image Analysis (IPRIA)\",\"volume\":\"115 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 3rd International Conference on Pattern Recognition and Image Analysis (IPRIA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/PRIA.2017.7983053\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 3rd International Conference on Pattern Recognition and Image Analysis (IPRIA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PRIA.2017.7983053","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, a new energy function has been proposed for tumor segmentation implemented by the level set method. Multi-scale Gaussian filter is applied to the image and its output determines the probability of each pixel belonging to the tumor structure. Introducing the output into the energy function makes the model robust against the inhomogeneous background. Experimental results from MRI verify the desirable performance of the proposed model in comparison with other methods.