A Study of Joint Space Narrowing and Erosion in Rheumatoid Arthritis

H. Kang, Kwang Gi Kim, J. Bae, Chang-Bu Jeong, Sungjun Kim
{"title":"A Study of Joint Space Narrowing and Erosion in Rheumatoid Arthritis","authors":"H. Kang, Kwang Gi Kim, J. Bae, Chang-Bu Jeong, Sungjun Kim","doi":"10.4258/JKSMI.2009.15.4.483","DOIUrl":null,"url":null,"abstract":"Objective: This study was conducted to measure radiographic joint space width and to estimate erosion in the hands of patients with rheumatoid arthritis. It showed that joint space width, homogeneity, and invariant moments are parameters to discriminate between the normal and the rheumatoid joint. Methods: In order to measure the joint space width and to estimate erosion in the finger joint, 32 radiographic images were used - 16 images for training and 16 images for testing. The joint space width was measured in order to quantify the joint space narrowing. Also, homogeneity and invariant moments was computed in order to quantify erosion. Finally, artificial neural networks were constructed and tested as a classifier distinguishing between the normal and the rheumatoid joint. Results: The joint space width of normal was 1.040.15 mm and the width of patients with rheumatoid arthritis was 0.940.15 mm. The Homogeneity of normal was 16568.832669.83 and invariant moments were 6843.452937.55. They were statistically difference (p<.05). Using these characteristics, artificial neural networks showed that they discriminate between normal and rheumatoid arthritis (AUC=0.91). Conclusion: Measuring joint space width, estimating homogeneity, and invariant moments provide the capability to distinguish between a normal joint and a rheumatoid joint.","PeriodicalId":255087,"journal":{"name":"Journal of Korean Society of Medical Informatics","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Korean Society of Medical Informatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4258/JKSMI.2009.15.4.483","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Objective: This study was conducted to measure radiographic joint space width and to estimate erosion in the hands of patients with rheumatoid arthritis. It showed that joint space width, homogeneity, and invariant moments are parameters to discriminate between the normal and the rheumatoid joint. Methods: In order to measure the joint space width and to estimate erosion in the finger joint, 32 radiographic images were used - 16 images for training and 16 images for testing. The joint space width was measured in order to quantify the joint space narrowing. Also, homogeneity and invariant moments was computed in order to quantify erosion. Finally, artificial neural networks were constructed and tested as a classifier distinguishing between the normal and the rheumatoid joint. Results: The joint space width of normal was 1.040.15 mm and the width of patients with rheumatoid arthritis was 0.940.15 mm. The Homogeneity of normal was 16568.832669.83 and invariant moments were 6843.452937.55. They were statistically difference (p<.05). Using these characteristics, artificial neural networks showed that they discriminate between normal and rheumatoid arthritis (AUC=0.91). Conclusion: Measuring joint space width, estimating homogeneity, and invariant moments provide the capability to distinguish between a normal joint and a rheumatoid joint.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
类风湿关节炎关节间隙狭窄和糜烂的研究
目的:本研究旨在测量类风湿关节炎患者手部关节间隙的x线片宽度,并评估其手部糜烂程度。关节间隙宽度、均匀性和不变矩是区分正常关节和类风湿关节的参数。方法:利用32张x线片测量指关节间隙宽度,估计指关节糜烂程度,其中16张用于训练,16张用于测试。测量关节间隙宽度,以量化关节间隙的缩小。此外,计算了均匀性和不变矩,以量化侵蚀。最后,构建了人工神经网络,并对其进行了测试,作为正常关节和类风湿关节的分类器。结果:正常人关节间隙宽度为1.040.15 mm,类风湿关节炎患者关节间隙宽度为0.940.15 mm。正态均匀性为16568.832669.83,不变矩为6843.452937.55。差异有统计学意义(p< 0.05)。利用这些特征,人工神经网络显示它们可以区分正常关节炎和类风湿关节炎(AUC=0.91)。结论:测量关节间隙宽度,估计均匀性和不变矩提供了区分正常关节和类风湿关节的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Assessing the Quality of Structured Data Entry for the Secondary Use of Electronic Medical Records A Korean Version of the WHO International Classification for Patient Safety: A Validity Study Development and Validation of Archetypes for Nursing Problems in Breast Cancer Patients Comparison of Physicians' and Patients' Perception on the Effect of Internet Health Information Practical Guide to Clinical Data Management by Susanne Prokscha, 2007
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1