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Yi Hu,Shinong Pan,Xudong Zhao,Wenli Guo,Ming He,Qiyong Guo 대한영상의학회 2017 Korean Journal of Radiology Vol.18 No.3
Objective: To evaluate orthopedic metal artifact reduction algorithm (O-MAR) in CT orthopedic metal artifact reduction at different tube voltages, identify an appropriate low tube voltage for clinical practice, and investigate its clinical application. Materials and Methods: The institutional ethical committee approved all the animal procedures. A stainless-steel plate and four screws were implanted into the femurs of three Japanese white rabbits. Preoperative CT was performed at 120 kVp without O-MAR reconstruction, and postoperative CT was performed at 80–140 kVp with O-MAR. Muscular CT attenuation, artifact index (AI) and signal-to-noise ratio (SNR) were compared between preoperative and postoperative images (unpaired t test), between paired O-MAR and non-O-MAR images (paired Student t test) and among different kVp settings (repeated measures ANOVA). Artifacts’ severity, muscular homogeneity, visibility of inter-muscular space and definition of bony structures were subjectively evaluated and compared (Wilcoxon rank-sum test). In the clinical study, 20 patients undertook CT scan at low kVp with O-MAR with informed consent. The diagnostic satisfaction of clinical images was subjectively assessed. Results: Animal experiments showed that the use of O-MAR resulted in accurate CT attenuation, lower AI, better SNR, and higher subjective scores (p < 0.010) at all tube voltages. O-MAR images at 100 kVp had almost the same AI and SNR as non-O-MAR images at 140 kVp. All O-MAR images were scored ≥ 3. In addition, 95% of clinical CT images performed at 100 kVp were considered satisfactory. Conclusion: O-MAR can effectively reduce orthopedic metal artifacts at different tube voltages, and facilitates low-tube-voltage CT for patients with orthopedic metal implants.
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Ming Jiang,Yunfei Li,Yuan Ge,Wengeng Gao,Ke Lou,Shinong Wang,Juanjuan Jiang 보안공학연구지원센터 2016 International Journal of Signal Processing, Image Vol.9 No.12
Position information is the foundation of massive applications in Wireless Sensor Network(WSN). Three improved positioning algorithms based on DV-Hop are proposed in order to enhance the positioning accuracy of wireless sensor nodes. First improved algorithm is distance compensation algorithm (DCA) that creates a triangle model to compensate the estimated distance. The second improved algorithm creates a new chain table for all anchor nodes to record and compute the average hop distance. The third improved algorithm is weighting different anchor nodes with anchor nodes’ nearest unknown nodes. The second and third improved algorithms are based on the DCA. The simulation results show that the three improved algorithms are better than the original DV-Hop in localization accuracy. Compared to the original DV-Hop algorithm, the simulation results shows that the three improved algorithms proposed in the paper increase the positioning accuracy of the unknown nodes.
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The Optimization of Genetic Algorithm in Wireless Sensor Network Coverage
Wengen Gao,Qigong Chen,Ming Jiang,Yunfei Li,Shinong Wang 보안공학연구지원센터(IJSIP) 2015 International Journal of Signal Processing, Image Vol.8 No.1
According to the maximum coverage problem in wireless sensor networks, GA algorithm combined with the standard processing method can improve the network coverage based on, but there is a risk of falling into local optimum, and costs more computation time. On the condition of analysis and proof of the effectiveness by the employment of normalization processing to resolve coding redundancy of MCSDP, further details of the evaluate conditions are proposed, and new parent selection mechanism is introduced, which both are verified by compared experiments. The experiment results show that the optimization processing method proposed in this paper retains the characteristics of existing methods, and has better optimization performance and improves the network coverage rate as well as calculation speed, which verifies the effectiveness and superiority of the method proposed in this paper.
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