亲爱的研友该休息了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!身体可是革命的本钱,早点休息,好梦!

Machine learning for lung CT texture analysis: Improvement of inter-observer agreement for radiological finding classification in patients with pulmonary diseases

医学 麦克内马尔试验 放射科 放射性武器 核医学 软件 统计 计算机科学 数学 程序设计语言
作者
Yoshiharu Ohno,Kota Aoyagi,Daisuke Takenaka,Takeshi Yoshikawa,Aina Ikezaki,Yasuko Fujisawa,Kazuhiro Murayama,Hidekazu Hattori,Hiroshi Toyama
出处
期刊:European Journal of Radiology [Elsevier BV]
卷期号:134: 109410-109410 被引量:22
标识
DOI:10.1016/j.ejrad.2020.109410
摘要

Abstract

Purpose

To evaluate the capability ML-based CT texture analysis for improving interobserver agreement and accuracy of radiological finding assessment in patients with COPD, interstitial lung diseases or infectious diseases.

Materials and methods

Training cases (n = 28), validation cases (n = 17) and test cases (n = 89) who underwent thin-section CT at a 320-detector row CT with wide volume scan and two 64-detector row CTs with helical scan were enrolled in this study. From 89 CT data, a total of 350 computationally selected ROI including normal lung, emphysema, nodular lesion, ground-glass opacity, reticulation and honeycomb were evaluated by three radiologists as well as by the software. Inter-observer agreements between consensus reading with and without using the software or software alone and standard references determined by consensus of pulmonologists and chest radiologists were determined using κ statistics. Overall distinguishing accuracies were compared among all methods by McNemar's test.

Results

Agreements for consensus readings obtained with and without the software or the software alone with standard references were determined as significant and substantial or excellent (with the software: κ = 0.91, p < 0.0001; without the software: κ = 0.81, p < 0.0001; the software alone: κ = 0.79, p < 0.0001). Overall differentiation accuracy of consensus reading using the software (94.9 [332/350] %) was significantly higher than that of consensus reading without using the software (84.3 [295/350] %, p < 0.0001) and the software alone (82.3 [288/350] %, p < 0.0001).

Conclusion

ML-based CT texture analysis software has potential for improving interobserver agreement and accuracy for radiological finding assessments in patients with COPD, interstitial lung diseases or infectious diseases.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
又来注水了完成签到,获得积分10
11秒前
快乐海豚完成签到 ,获得积分10
17秒前
科研通AI5应助科研通管家采纳,获得10
21秒前
科研狗的春天完成签到 ,获得积分10
24秒前
Lucas应助董可以采纳,获得10
31秒前
37秒前
Aqib发布了新的文献求助10
42秒前
43秒前
科研通AI5应助西瓜嘻嘻嘻采纳,获得10
46秒前
吴昕昕发布了新的文献求助10
48秒前
未晚完成签到 ,获得积分10
50秒前
香蕉觅云应助Aqib采纳,获得10
54秒前
早晨发布了新的文献求助10
1分钟前
孤鸿.完成签到 ,获得积分10
1分钟前
1分钟前
彭于晏应助11采纳,获得10
1分钟前
1分钟前
吴昕昕完成签到,获得积分10
1分钟前
1分钟前
iwaking完成签到,获得积分10
1分钟前
hxn发布了新的文献求助30
1分钟前
通通发布了新的文献求助10
1分钟前
早晨完成签到,获得积分10
1分钟前
Lucas应助通通采纳,获得10
1分钟前
1分钟前
WANG完成签到,获得积分10
1分钟前
有机发布了新的文献求助10
1分钟前
摆渡人完成签到,获得积分10
1分钟前
提桶跑路完成签到 ,获得积分10
1分钟前
温柔的天奇完成签到 ,获得积分10
1分钟前
实验耗材完成签到 ,获得积分10
1分钟前
1分钟前
lhlhl完成签到,获得积分10
1分钟前
1分钟前
1分钟前
小小林发布了新的文献求助10
2分钟前
zl13332完成签到 ,获得积分10
2分钟前
2分钟前
通通完成签到 ,获得积分10
2分钟前
hhh完成签到 ,获得积分10
2分钟前
高分求助中
The Mother of All Tableaux: Order, Equivalence, and Geometry in the Large-scale Structure of Optimality Theory 3000
A new approach to the extrapolation of accelerated life test data 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
基于可调谐半导体激光吸收光谱技术泄漏气体检测系统的研究 350
Robot-supported joining of reinforcement textiles with one-sided sewing heads 320
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3990020
求助须知:如何正确求助?哪些是违规求助? 3532077
关于积分的说明 11256276
捐赠科研通 3270943
什么是DOI,文献DOI怎么找? 1805139
邀请新用户注册赠送积分活动 882270
科研通“疑难数据库(出版商)”最低求助积分说明 809228