{"title":"一种基于爱的FCM算法用于胆结石CT图像分割","authors":"Wang Hong-yan, Lv Ji-xing","doi":"10.1109/ICCSE.2015.7250345","DOIUrl":null,"url":null,"abstract":"To acquire more accurate CT image segmentation results of gallstone, this paper presents a Lore-Based FCM algorithm to conquer the deficiency of tradition FCM method. A penalty term is introduced to objective function to enlarge the range of specified class and achieve higher segmentation accuracy. The result of simulation shows that Lore-Based FCM can obviously improve the segmentation quality. The improved algorithm is more rapid and efficiency than the traditional FCM.","PeriodicalId":311451,"journal":{"name":"2015 10th International Conference on Computer Science & Education (ICCSE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A lore-based FCM algorithm for gallstone CT images segmentation\",\"authors\":\"Wang Hong-yan, Lv Ji-xing\",\"doi\":\"10.1109/ICCSE.2015.7250345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To acquire more accurate CT image segmentation results of gallstone, this paper presents a Lore-Based FCM algorithm to conquer the deficiency of tradition FCM method. A penalty term is introduced to objective function to enlarge the range of specified class and achieve higher segmentation accuracy. The result of simulation shows that Lore-Based FCM can obviously improve the segmentation quality. The improved algorithm is more rapid and efficiency than the traditional FCM.\",\"PeriodicalId\":311451,\"journal\":{\"name\":\"2015 10th International Conference on Computer Science & Education (ICCSE)\",\"volume\":\"67 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-07-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 10th International Conference on Computer Science & Education (ICCSE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSE.2015.7250345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 10th International Conference on Computer Science & Education (ICCSE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2015.7250345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A lore-based FCM algorithm for gallstone CT images segmentation
To acquire more accurate CT image segmentation results of gallstone, this paper presents a Lore-Based FCM algorithm to conquer the deficiency of tradition FCM method. A penalty term is introduced to objective function to enlarge the range of specified class and achieve higher segmentation accuracy. The result of simulation shows that Lore-Based FCM can obviously improve the segmentation quality. The improved algorithm is more rapid and efficiency than the traditional FCM.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
