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4,131 results on '"Zheng, Rui"'

105. Automatic segmentation of vertebral features on ultrasound spine images using Stacked Hourglass Network

Author

Zeng, Hong-Ye, Ge, Song-Han, Gao, Yu-Chong, Zhou, De-Sen, Zhou, Kang, He, Xu-Ming, Lou, Edmond, and Zheng, Rui

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition
Abstract

Objective: The spinous process angle (SPA) is one of the essential parameters to denote three-dimensional (3-D) deformity of spine. We propose an automatic segmentation method based on Stacked Hourglass Network (SHN) to detect the spinous processes (SP) on ultrasound (US) spine images and to measure the SPAs of clinical scoliotic subjects. Methods: The network was trained to detect vertebral SP and laminae as five landmarks on 1200 ultrasound transverse images and validated on 100 images. All the processed transverse images with highlighted SP and laminae were reconstructed into a 3D image volume, and the SPAs were measured on the projected coronal images. The trained network was tested on 400 images by calculating the percentage of correct keypoints (PCK); and the SPA measurements were evaluated on 50 scoliotic subjects by comparing the results from US images and radiographs. Results: The trained network achieved a high average PCK (86.8%) on the test datasets, particularly the PCK of SP detection was 90.3%. The SPAs measured from US and radiographic methods showed good correlation (r>0.85), and the mean absolute differences (MAD) between two modalities were 3.3{\deg}, which was less than the clinical acceptance error (5{\deg}). Conclusion: The vertebral features can be accurately segmented on US spine images using SHN, and the measurement results of SPA from US data was comparable to the gold standard from radiography., Comment: 9 pages,5 figures

Published
2021

106. Assessing Bone Quality of Spine on Children with Scoliosis Using Ultrasound Reflection FAI Method -- A Preliminary Study

Author

Song, Sheng, Chen, Hongbo, Li, Conger, Lou, Edmond, Le, Lawrence H, and Zheng, Rui

Subjects
Physics - Medical Physics
Abstract

Osteopenia is indicated as a common phenomenon in patients who have scoliosis. Quantitative ultrasound (QUS) has been used to assess skeletal status for decades, and recently ultrasound imaging using reflection signals from vertebra were as well applied to measure spinal curvatures on children with scoliosis. The objectives of this study are to develop a new method which can robustly extract a parameter from ultrasound spinal data for estimating bone quality of scoliotic patients and to investigate the potential for the parameter on predicting curve progression. The frequency amplitude index (FAI) was calculated based on the spectrum of the original radio frequency (RF) signals reflected from the tissue-vertebra interface. The correlation between FAI and reflection coefficient was validated using decalcified bovine bone samples in vitro, and the FAIs of scoliotic subjects were investigated in vivo referring to BMI, Cobb angles and curve progression status. The results showed that the intra-rater measures were highly reliable between different trials (ICC=0.997). The FAI value was strongly correlated to the reflection coefficient of bone tissue ($R^{2}=0.824$), and the lower FAI indicated the higher risk of curve progression for the non-mild cases. This preliminary study reported that the FAI method can provide a feasible and promising approach to assess bone quality and monitor curve progression of the patients who have AIS., Comment: typos corrected, positions of figures' captions corrected

Published
2021
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107. Construction of Control System on Kinematic Redundant Hybrid Parallel Mechanism for Micro-assembly

Author

Zhang, Fen-hua, Zhang, Xian-min, Zheng, Rui-da, Xie, Tian-yu, Zhang, Jian-qin, Li, Hai, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Yang, Huayong, editor, Liu, Honghai, editor, Zou, Jun, editor, Yin, Zhouping, editor, Liu, Lianqing, editor, Yang, Geng, editor, Ouyang, Xiaoping, editor, and Wang, Zhiyong, editor

Published
2023
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108. The Influence of Interpersonal Conflict on Organizational Members: An Analysis Based on the Chain Mediation Model

Author

Chang, Lin, Tao, Rui, Zheng, Rui, Li, Kan, Editor-in-Chief, Li, Qingyong, Associate Editor, Fournier-Viger, Philippe, Series Editor, Hong, Wei-Chiang, Series Editor, Liang, Xun, Series Editor, Wang, Long, Series Editor, Xu, Xuesong, Series Editor, Khan, Syed Abdul Rehman, editor, Jhanjhi, Noor Zaman, editor, and Li, Hongbo, editor

Published
2023
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119. TextFlint: Unified Multilingual Robustness Evaluation Toolkit for Natural Language Processing

Author

Gui, Tao, Wang, Xiao, Zhang, Qi, Liu, Qin, Zou, Yicheng, Zhou, Xin, Zheng, Rui, Zhang, Chong, Wu, Qinzhuo, Ye, Jiacheng, Pang, Zexiong, Zhang, Yongxin, Li, Zhengyan, Ma, Ruotian, Fei, Zichu, Cai, Ruijian, Zhao, Jun, Hu, Xingwu, Yan, Zhiheng, Tan, Yiding, Hu, Yuan, Bian, Qiyuan, Liu, Zhihua, Zhu, Bolin, Qin, Shan, Xing, Xiaoyu, Fu, Jinlan, Zhang, Yue, Peng, Minlong, Zheng, Xiaoqing, Zhou, Yaqian, Wei, Zhongyu, Qiu, Xipeng, and Huang, Xuanjing

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

Various robustness evaluation methodologies from different perspectives have been proposed for different natural language processing (NLP) tasks. These methods have often focused on either universal or task-specific generalization capabilities. In this work, we propose a multilingual robustness evaluation platform for NLP tasks (TextFlint) that incorporates universal text transformation, task-specific transformation, adversarial attack, subpopulation, and their combinations to provide comprehensive robustness analysis. TextFlint enables practitioners to automatically evaluate their models from all aspects or to customize their evaluations as desired with just a few lines of code. To guarantee user acceptability, all the text transformations are linguistically based, and we provide a human evaluation for each one. TextFlint generates complete analytical reports as well as targeted augmented data to address the shortcomings of the model's robustness. To validate TextFlint's utility, we performed large-scale empirical evaluations (over 67,000 evaluations) on state-of-the-art deep learning models, classic supervised methods, and real-world systems. Almost all models showed significant performance degradation, including a decline of more than 50% of BERT's prediction accuracy on tasks such as aspect-level sentiment classification, named entity recognition, and natural language inference. Therefore, we call for the robustness to be included in the model evaluation, so as to promote the healthy development of NLP technology.

Published
2021

122. ABLs and TMKs are co-receptors for extracellular auxin

Author

Yu, Yongqiang, Tang, Wenxin, Lin, Wenwei, Li, Wei, Zhou, Xiang, Li, Ying, Chen, Rong, Zheng, Rui, Qin, Guochen, Cao, Wenhan, Pérez-Henríquez, Patricio, Huang, Rongfeng, Ma, Jun, Qiu, Qiqi, Xu, Ziwei, Zou, Ailing, Lin, Juncheng, Jiang, Liwen, Xu, Tongda, and Yang, Zhenbiao

Published
2023
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135. Effectiveness of Parent-Training Program on Children with Autism Spectrum Disorder in China

Author

Liang, Shuang, Zheng, Rui-Xuan, Zhang, Li-Li, Liu, Yi-Mei, Ge, Ke-Juan, Zhou, Zi-Yun, and Wang, Lei

Abstract

Objective: This study intends to explore the effect of parent-training program on the rehabilitation intervention in children with autism spectrum disorder (ASD) in Chinese-speaking areas of China by offering parent skill training and psychology counseling. Methods: From January 2018 to June 2019, a total of 80 children diagnosed with ASD from the Department of Children Healthcare of Wuxi Children's Hospital were randomly grouped into the parent training groups and control groups. Parents in the training group received 12 weeks of skill training, including 8 group and 2 individual training sessions, as well as psychology counseling. This enabled them to give their children >2 h of intervention training daily in a natural environment. Children in the control group were placed on a rehabilitation waiting list or received general community training. Before grouping and after the intervention, all children underwent neuropsychological evaluations with Autism Behavior Checklist (ABC), Childhood Autism Rating Scale (CARS), and Gesell Developmental Schedule (GDS). GDS covers five sectors, namely adaptive behavior, gross motor, fine motor, language, and personal-social behavior. Results: Statistically significant differences were not detected between the two groups in ABC, CARS, and GDS scoring at baseline evaluation. And significant differences were detected between the two groups in ABC, CARS, adaptive behavior, and personal-social behavior scoring at endpoint evaluation. Furthermore, the re-evaluation results of ABC scoring and CARS scoring of the children in the parent training group decreased significantly from the preliminary evaluation results when compared before and after the intervention. Moreover, the intragroup comparison of adaptive behavior scoring, language scoring, and personal-social behavior scoring of the experiment group increased significantly from the preliminary evaluation results, while the difference of the same of the children in the control group between re-evaluation and preliminary evaluation did not differ significantly. Conclusions: In China, the parent-training program enables parents to train ASD children in a natural environment, which would markedly improve behavioral problems, core symptoms, adaptability, language competence, and social development capability.

Published
2022
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