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- 저자 : Zhou Yiran (검색결과 3 건)
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Feasibility of a Clinical-Radiomics Model to Predict the Outcomes of Acute Ischemic Stroke
Zhou Yiran,Wu Di,Yan Su,Xie Yan,Zhang Shun,Lv Wenzhi,Qin Yuanyuan,Liu Yufei,Liu Chengxia,Lu Jun,Li Jia,Zhu Hongquan,Liu Weiyin Vivian,Liu Huan,Zhang Guiling,Zhu Wenzhen 대한영상의학회 2022 Korean Journal of Radiology Vol.23 No.8
Objective: To develop a model incorporating radiomic features and clinical factors to accurately predict acute ischemic stroke (AIS) outcomes. Materials and Methods: Data from 522 AIS patients (382 male [73.2%]; mean age ± standard deviation, 58.9 ± 11.5 years) were randomly divided into the training (n = 311) and validation cohorts (n = 211). According to the modified Rankin Scale (mRS) at 6 months after hospital discharge, prognosis was dichotomized into good (mRS ≤ 2) and poor (mRS > 2); 1310 radiomics features were extracted from diffusion-weighted imaging and apparent diffusion coefficient maps. The minimum redundancy maximum relevance algorithm and the least absolute shrinkage and selection operator logistic regression method were implemented to select the features and establish a radiomics model. Univariable and multivariable logistic regression analyses were performed to identify the clinical factors and construct a clinical model. Ultimately, a multivariable logistic regression analysis incorporating independent clinical factors and radiomics score was implemented to establish the final combined prediction model using a backward step-down selection procedure, and a clinical-radiomics nomogram was developed. The models were evaluated using calibration, receiver operating characteristic (ROC), and decision curve analyses. Results: Age, sex, stroke history, diabetes, baseline mRS, baseline National Institutes of Health Stroke Scale score, and radiomics score were independent predictors of AIS outcomes. The area under the ROC curve of the clinical-radiomics model was 0.868 (95% confidence interval, 0.825–0.910) in the training cohort and 0.890 (0.844–0.936) in the validation cohort, which was significantly larger than that of the clinical or radiomics models. The clinical radiomics nomogram was well calibrated (p > 0.05). The decision curve analysis indicated its clinical usefulness. Conclusion: The clinical-radiomics model outperformed individual clinical or radiomics models and achieved satisfactory performance in predicting AIS outcome
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Design and Application of Small Scale Cluster System Based on OpenFOAM
Yiran Wang,Wengang Zhou 보안공학연구지원센터 2015 International Journal of Hybrid Information Techno Vol.8 No.2
In order to solve the simulation problem of steady compressible turbulent combustion, a small scale high performance parallel cluster system was designed. It based on the open source CFD platform OpenFOAM, and was used to to simulate the bluff-body stabilized Sydney flame hm1 which refers to the detailed chemical kinetic mechanisms of coal gas and air combustion reaction. The flow of combustion reaction component concentration distribution and temperature curve diagram are plotted according to the computational results. The comparison between the simulation and the experimental results shows that this parallel cluster system has efficient computation for steady compressible turbulent combustion flow.
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Reflection-type Finger Vein Recognition for Mobile Applications
Congcong Zhang,Zhi Liu,Yi Liu,Fangqi Su,Jun Chang,Yiran Zhou,Qijun Zhao 한국광학회 2015 Current Optics and Photonics Vol.19 No.5
Finger vein recognition, which is a promising biometric method for identity authentication, has attractedsignificant attention. Considerable research focuses on transmission-type finger vein recognition, but thistype of authentication is difficult to implement in mobile consumer devices. Therefore, reflection-type fingervein recognition should be developed. In the reflection-type vein recognition field, the majority ofresearchers concentrate on palm and palm dorsa patterns, and only a few pay attention to reflection-typefinger vein recognition. Thus, this paper presents reflection-type finger vein recognition for biometricapplication that can be integrated into mobile consumer devices. A database is built to test the proposedalgorithm. A novel method of region-of-interest localization for a finger vein image is introduced, anda scheme for effectively extracting finger vein features is proposed. Experiments demonstrate the feasibilityof reflection-type finger vein recognition
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