超声图像中甲状腺结节的计算机辅助检测

D. Maroulis, M. Savelonas, S. Karkanis, Dimitrios K. Iakovidis, N. Dimitropoulos
{"title":"超声图像中甲状腺结节的计算机辅助检测","authors":"D. Maroulis, M. Savelonas, S. Karkanis, Dimitrios K. Iakovidis, N. Dimitropoulos","doi":"10.1109/CBMS.2005.44","DOIUrl":null,"url":null,"abstract":"Nodular thyroid disease is a frequent occurrence in clinical practice and it is associated with increased risk of thyroid cancer and hyperfunction. In this paper we propose a novel method for computer-aided detection of thyroid nodules in ultrasound (US) images. The proposed method is based on a level-set image segmentation approach that takes into account the inhomogeneity of the US images. This novel method was experimentally evaluated using US images acquired from 35 patients. The results show that the proposed method achieves more accurate delineation of the thyroid nodules in the US images and faster convergence than other relevant methods.","PeriodicalId":119367,"journal":{"name":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2005-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"45","resultStr":"{\"title\":\"Computer-aided thyroid nodule detection in ultrasound images\",\"authors\":\"D. Maroulis, M. Savelonas, S. Karkanis, Dimitrios K. Iakovidis, N. Dimitropoulos\",\"doi\":\"10.1109/CBMS.2005.44\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nodular thyroid disease is a frequent occurrence in clinical practice and it is associated with increased risk of thyroid cancer and hyperfunction. In this paper we propose a novel method for computer-aided detection of thyroid nodules in ultrasound (US) images. The proposed method is based on a level-set image segmentation approach that takes into account the inhomogeneity of the US images. This novel method was experimentally evaluated using US images acquired from 35 patients. The results show that the proposed method achieves more accurate delineation of the thyroid nodules in the US images and faster convergence than other relevant methods.\",\"PeriodicalId\":119367,\"journal\":{\"name\":\"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2005-06-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"45\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CBMS.2005.44\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2005.44","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 45

摘要

甲状腺结节性疾病是临床上常见的疾病,它与甲状腺癌和功能亢进的风险增加有关。在本文中,我们提出了一种计算机辅助检测甲状腺结节超声图像的新方法。所提出的方法是基于考虑到美国图像的非均匀性的水平集图像分割方法。采用35例患者的超声图像对这种新方法进行了实验评估。结果表明,与其他相关方法相比,该方法能够更准确地描绘甲状腺结节的US图像,并且收敛速度更快。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer-aided thyroid nodule detection in ultrasound images
Nodular thyroid disease is a frequent occurrence in clinical practice and it is associated with increased risk of thyroid cancer and hyperfunction. In this paper we propose a novel method for computer-aided detection of thyroid nodules in ultrasound (US) images. The proposed method is based on a level-set image segmentation approach that takes into account the inhomogeneity of the US images. This novel method was experimentally evaluated using US images acquired from 35 patients. The results show that the proposed method achieves more accurate delineation of the thyroid nodules in the US images and faster convergence than other relevant methods.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信