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- 저자 : Yih-Shyh (검색결과 3 건)
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Diagnosis of Pulmonary Arterial Hypertension in Children by Using Cardiac Computed Tomography
Shyh-Jye Chen,Jou-Hsuan Huang,Wen-Jeng Lee,Ming-Tai Lin,Yih-Sharng Chen,Jou-Kou Wang 대한영상의학회 2019 Korean Journal of Radiology Vol.20 No.6
Objective: To establish diagnostic criteria for pulmonary arterial hypertension (PAH) in children by using parameters obtained through noninvasive cardiac computed tomography (CCT). Materials and Methods: We retrospectively measured parameters from CCT images of children from a single institution in a multiple stepwise process. A total of 208 children with mean age of 10.5 years (range: 4 days–18.9 years) were assessed. The variables were classified into three groups: the great arteries; the ventricular walls; and the bilateral ventricular cavities. The relationship between the parameters obtained from the CCT images and mean pulmonary arterial pressure (mPAP) was tested and adjusted by the children’s body size. Reference curves for the pulmonary trunk diameter (PTD) and ratio of diameter of pulmonary trunk to ascending aorta (rPTAo) of children with CCT images of normal hearts, adjusted for height, were plotted. Threshold lines were established on the reference curves. Results: PTD and rPTAo on the CCT images were significantly positively correlated with mPAP (r > 0.85, p < 0.01). Height was the body size parameter most correlated with PTD (r = 0.91, p < 0.01) and rPTAo (r = -0.69, p < 0.01). On the basis of the threshold lines on the reference curves, PTD and rPTAo both showed 88.9% sensitivity for PAH diagnosis, with negative predictive values of 93.3% and 92.9%, respectively. Conclusion: PTD and rPTAo measured from CCT images were significantly correlated with mPAP in children. Reference curves and the formula of PTD and rPTAo adjusted for height could be practical for diagnosing PAH in children.
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Sheng-Cheng Yeh,Yih-Shyh Chiou,Huan Chang,Wang-Hsin Hsu,Shiau-Huang Liu,Fuan Tsai 한국통신학회 2016 Journal of communications and networks Vol.18 No.5
Providing a customer with tailored location-based ser-vices (LBSs) is a fundamental problem. For location-estimationtechniques with radio-based measurements, LBS applications arewidely available for mobile devices (MDs), such as smartphones,enabling users to run multi-task applications. LBS information notonly enables obtaining the current location of an MD but also pro-vides real-time push-pull communication service. For indoor envi-ronments, localization technologies based on radio frequency (RF)pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching ap-proaches, a considerable amount of time and work is spent in in-door environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposesan indoor positioning approach, which involves using Asus Xtionto facilitate capturing RF signals during an offline site survey. Thedepth information obtained using Asus Xtion is utilized to estimatethe locations and predict the received signal strength (RF informa-tion) at uncertain locations. The proposed approach effectively re-duces not only the time and work costs but also the computing com-plexity involved in determining the orientation and RF during theonline positioning phase by estimating the user’s location by usinga smartphone. The experimental results demonstrated that morethan 78% of time was saved, and the number of samples acquiredusing the proposed method during the offline phase was twice asmuch as that acquired using the conventional method. For the on-line phase, the location estimates have error distances of less than2.67 m. Therefore, the proposed approach is beneficial for use invarious LBS applications.
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Yeh, Sheng-Cheng,Chiou, Yih-Shyh,Chang, Huan,Hsu, Wang-Hsin,Liu, Shiau-Huang,Tsai, Fuan The Korea Institute of Information and Commucation 2016 Journal of communications and networks Vol.18 No.5
Providing a customer with tailored location-based services (LBSs) is a fundamental problem. For location-estimation techniques with radio-based measurements, LBS applications are widely available for mobile devices (MDs), such as smartphones, enabling users to run multi-task applications. LBS information not only enables obtaining the current location of an MD but also provides real-time push-pull communication service. For indoor environments, localization technologies based on radio frequency (RF) pattern-matching approaches are accurate and commonly used. However, to survey radio information for pattern-matching approaches, a considerable amount of time and work is spent in indoor environments. Consequently, in order to reduce the system-deployment cost and computing complexity, this article proposes an indoor positioning approach, which involves using Asus Xtion to facilitate capturing RF signals during an offline site survey. The depth information obtained using Asus Xtion is utilized to estimate the locations and predict the received signal strength (RF information) at uncertain locations. The proposed approach effectively reduces not only the time and work costs but also the computing complexity involved in determining the orientation and RF during the online positioning phase by estimating the user's location by using a smartphone. The experimental results demonstrated that more than 78% of time was saved, and the number of samples acquired using the proposed method during the offline phase was twice as much as that acquired using the conventional method. For the online phase, the location estimates have error distances of less than 2.67 m. Therefore, the proposed approach is beneficial for use in various LBS applications.
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