返回
Computer-Aided System Application Value for Assessing Hip Development
DOI:10.3389/fphys.2020.587161.png)
摘要
En 中文
Purpose A computer-aided system was used to semiautomatically measure Tonnis angle, Sharp angle, and center-edge (CE) angle using contours of the hip bones to establish an auxiliary measurement model for developmental screening or diagnosis of hip joint disorders. Methods We retrospectively analyzed bilateral hip x-rays for 124 patients (41 men and 83 women aged 20-70 years) who presented at the Affiliated Zhongshan Hospital of Dalian University in 2017 and 2018. All images were imported into a computer-aided detection system. After manually outlining hip bone contours, Tonnis angle, Sharp angle, and CE angle marker lines were automatically extracted, and the angles were measured and recorded. An imaging physician also manually measured all angles and recorded hip development, and Pearson correlation coefficients were used to compare computer-aided system measurements with imaging physician measurements. Accuracy for different angles was calculated, and the area under the receiver operating characteristic (AUROC) curve was used to represent the diagnostic efficiency of the computer-aided system. Results For Tonnis angle, Sharp angle, and CE angle, correlation coefficients were 0.902, 0.887, and 0.902, respectively; the accuracies of the computer-aided detection system were 89.1, 93.1, and 82.3%; and the AUROC curve values were 0.940, 0.956, and 0.948. Conclusion The measurements of Tonnis angle, Sharp angle, and CE angle using the semiautomatic system were highly correlated with the measurements of the imaging physician and can be used to assess hip joint development with high accuracy and diagnostic efficiency.
Keyword:
hip dysplasia
acetabular dysplasia
computer-aided detection
computer-aided diagnosis
x-ray
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
3.4
论文数:
2.0W
被引数:
6.2W
机构
引用论文
A Kinetic Model with Ordered Cytoplasmic Dissociation for SUC1, an Arabidopsis H + /Sucrose Cotransporter Expressed in Xenopus Oocytes在非洲爪蟾卵母细胞中表达的拟南芥H/蔗糖协同转运蛋白SUC1的有序细胞质解离动力学模型
Current Applications and Future Impact of Machine Learning in Radiology机器学习在放射学中的当前应用和未来影响
RADIOLOGY
IF15.2

