基于计算机的多发性硬化症病灶分割、变化检测与量化

E. Goceri, Caner Songül
{"title":"基于计算机的多发性硬化症病灶分割、变化检测与量化","authors":"E. Goceri, Caner Songül","doi":"10.1109/UBMK.2017.8093371","DOIUrl":null,"url":null,"abstract":"Multiple Sclerosis (MS) is a neurological, progressive widespread disease whose diagnosis, treatment and monitoring have vital importance. However, manual method based on visual inspection for diagnosis and time-series assessments of changes in MS lesions is not re-producible and quantitative. Also, it is subjective and yields in inter-/intra-observer variabilities. Furthermore, the conventional method is time-consuming and mostly urgent results are required in practice. Therefore, in the literature, automated techniques have been proposed to detect and segment MS lesions and also to evaluate changes in these lesions quantitatively. In this paper, these automated approaches are presented for the radiologists, neurologists and researchers who are interested in this subject or want to improve former works or want to develop novel automated methods to overcome the problems in this active research area.","PeriodicalId":201903,"journal":{"name":"2017 International Conference on Computer Science and Engineering (UBMK)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Computer-based segmentation, change detection and quantification for lesions in multiple sclerosis\",\"authors\":\"E. Goceri, Caner Songül\",\"doi\":\"10.1109/UBMK.2017.8093371\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Multiple Sclerosis (MS) is a neurological, progressive widespread disease whose diagnosis, treatment and monitoring have vital importance. However, manual method based on visual inspection for diagnosis and time-series assessments of changes in MS lesions is not re-producible and quantitative. Also, it is subjective and yields in inter-/intra-observer variabilities. Furthermore, the conventional method is time-consuming and mostly urgent results are required in practice. Therefore, in the literature, automated techniques have been proposed to detect and segment MS lesions and also to evaluate changes in these lesions quantitatively. In this paper, these automated approaches are presented for the radiologists, neurologists and researchers who are interested in this subject or want to improve former works or want to develop novel automated methods to overcome the problems in this active research area.\",\"PeriodicalId\":201903,\"journal\":{\"name\":\"2017 International Conference on Computer Science and Engineering (UBMK)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Conference on Computer Science and Engineering (UBMK)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UBMK.2017.8093371\",\"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 International Conference on Computer Science and Engineering (UBMK)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UBMK.2017.8093371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

摘要

多发性硬化症(MS)是一种神经系统进行性广泛疾病,其诊断、治疗和监测具有至关重要的意义。然而,基于视觉检查的诊断和MS病变变化的时间序列评估的人工方法是不可重复和定量的。此外,它是主观的,产生了观察者之间/内部的变量。此外,传统的方法耗时长,而且在实际应用中大多需要紧急的结果。因此,在文献中,已经提出了自动化技术来检测和分割MS病变,并定量评估这些病变的变化。在本文中,这些自动化方法是为对这一主题感兴趣或想要改进以前的工作或想要开发新的自动化方法来克服这一活跃研究领域的问题的放射科医生,神经科医生和研究人员提供的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Computer-based segmentation, change detection and quantification for lesions in multiple sclerosis
Multiple Sclerosis (MS) is a neurological, progressive widespread disease whose diagnosis, treatment and monitoring have vital importance. However, manual method based on visual inspection for diagnosis and time-series assessments of changes in MS lesions is not re-producible and quantitative. Also, it is subjective and yields in inter-/intra-observer variabilities. Furthermore, the conventional method is time-consuming and mostly urgent results are required in practice. Therefore, in the literature, automated techniques have been proposed to detect and segment MS lesions and also to evaluate changes in these lesions quantitatively. In this paper, these automated approaches are presented for the radiologists, neurologists and researchers who are interested in this subject or want to improve former works or want to develop novel automated methods to overcome the problems in this active research area.
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:604180095
Book学术官方微信