采用AM-FM模型的MRI脑图像分割

Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154) Pub Date : 2000-10-29 DOI:10.1109/ACSSC.2000.910646

M.S. Patichis, H. Petropoulos, W. Brooks

{"title":"采用AM-FM模型的MRI脑图像分割","authors":"M.S. Patichis, H. Petropoulos, W. Brooks","doi":"10.1109/ACSSC.2000.910646","DOIUrl":null,"url":null,"abstract":"MRI brain images are characterized by non-stationary components that make fully automated segmentation a challenging task. An AM-FM model is used to model these non-stationarities. Using the AM-FM model, a new, fully automated texture segmentation system is used to automatically segment the cerebellum from a 3-D set of MRI brain images.","PeriodicalId":10581,"journal":{"name":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","volume":"6 1","pages":"906-910 vol.2"},"PeriodicalIF":0.0000,"publicationDate":"2000-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MRI brain image segmentation using an AM-FM model\",\"authors\":\"M.S. Patichis, H. Petropoulos, W. Brooks\",\"doi\":\"10.1109/ACSSC.2000.910646\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"MRI brain images are characterized by non-stationary components that make fully automated segmentation a challenging task. An AM-FM model is used to model these non-stationarities. Using the AM-FM model, a new, fully automated texture segmentation system is used to automatically segment the cerebellum from a 3-D set of MRI brain images.\",\"PeriodicalId\":10581,\"journal\":{\"name\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"volume\":\"6 1\",\"pages\":\"906-910 vol.2\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2000-10-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ACSSC.2000.910646\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACSSC.2000.910646","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

MRI脑图像具有非平稳成分的特点，使全自动分割成为一项具有挑战性的任务。采用AM-FM模型对这些非平稳性进行建模。利用AM-FM模型，一种新的全自动纹理分割系统被用于从一组三维MRI脑图像中自动分割小脑。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

MRI brain image segmentation using an AM-FM model

MRI brain images are characterized by non-stationary components that make fully automated segmentation a challenging task. An AM-FM model is used to model these non-stationarities. Using the AM-FM model, a new, fully automated texture segmentation system is used to automatically segment the cerebellum from a 3-D set of MRI brain images.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers (Cat. No.00CH37154)

自引率

0.00%

发文量