目的探讨多模型迭代重建技术对早期肺癌低剂量GE revolution CT成像质量的影响。方法将2018年1月~2019年6月于北京世纪坛医院就诊的240例早期肺癌患者作为观察对象,所有患者均行低剂量GE revolution CT成像检查,并采用多模型迭代重建技...目的探讨多模型迭代重建技术对早期肺癌低剂量GE revolution CT成像质量的影响。方法将2018年1月~2019年6月于北京世纪坛医院就诊的240例早期肺癌患者作为观察对象,所有患者均行低剂量GE revolution CT成像检查,并采用多模型迭代重建技术对图像进行重建。比较图像重建前后肺窗图像质量、纵膈窗图像质量及图像质量参数。结果与低剂量GE revolution CT图像相比,应用多模型迭代重建技术重建后的肺窗和纵膈窗图像质量提高,图像噪声降低(8.83±1.95 Hu vs 9.21±2.17 Hu),信噪比升高(7.21±1.30 vs 6.89±1.22),差异均有统计学意义(P<0.05),而CT值比较差异无统计学意义(65.01±7.94 Hu vs 65.38±8.26 Hu,P>0.05)。结论多模型迭代重建技术能够提高早期肺癌低剂量GE revolution CT成像质量,对早期肺癌的筛查具有重要临床应用价值。展开更多
The pyramidal multiphase level set framework （PMLSF） based on the technique of painting background （TPBG） and the Chan-Vese model can detect multiple objects on a given image. However, the boundaries of the sub-ob...The pyramidal multiphase level set framework （PMLSF） based on the technique of painting background （TPBG） and the Chan-Vese model can detect multiple objects on a given image. However, the boundaries of the sub-object obtained by PMLSF-TPBG are not variable since a specialcolor parameter is used in TPBG. To solve the problem, a new technique utilizing a varying parameter is proposed to ensure that PMLSF is effective for the detection of the desired boundaries of the sub-object. The interval of the variable color parameter is proved and the effects of the parameter are also discussed. Experimental results for the brain tumor detection show that different boundaries of the brain tumors can be detected with different color parameters. It is especially useful for clinical diagnoses.展开更多
This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscente...This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.展开更多
Along with the development of motion capture technique, more and more 3D motion databases become available. In this paper, a novel approach is presented for motion recognition and retrieval based on ensemble HMM (hidd...Along with the development of motion capture technique, more and more 3D motion databases become available. In this paper, a novel approach is presented for motion recognition and retrieval based on ensemble HMM (hidden Markov model) learning. Due to the high dimensionality of motion’s features, Isomap nonlinear dimension reduction is used for training data of ensemble HMM learning. For handling new motion data, Isomap is generalized based on the estimation of underlying eigen- functions. Then each action class is learned with one HMM. Since ensemble learning can effectively enhance supervised learning, ensembles of weak HMM learners are built. Experiment results showed that the approaches are effective for motion data recog- nition and retrieval.展开更多
Internet multi-robotics is a typical discrete-event system. In order to describe joint activities between multiple operators and multiple robots, a 4-level discrete-event model is proposed in this paper based on the c...Internet multi-robotics is a typical discrete-event system. In order to describe joint activities between multiple operators and multiple robots, a 4-level discrete-event model is proposed in this paper based on the controlled condition/event Petri nets (CCEP). On the first or mission level, the task splitting of the system is defined; on the second or multi-operator level, a precedence graph is introduced for every operator to plan his or her robotic actions; on the third or coordination level, the above precedence graphs are translated and integrated into the corresponding CCEPs in terms of specific rules; and on the last or multi-robot level, operators can select their control range by setting the corresponding control marks of the obtained CCEPs. As a consequence, a clear mechanism of operator-robot collaboration is obtained to conduct the development of the system.展开更多
文摘目的探讨多模型迭代重建技术对早期肺癌低剂量GE revolution CT成像质量的影响。方法将2018年1月~2019年6月于北京世纪坛医院就诊的240例早期肺癌患者作为观察对象,所有患者均行低剂量GE revolution CT成像检查,并采用多模型迭代重建技术对图像进行重建。比较图像重建前后肺窗图像质量、纵膈窗图像质量及图像质量参数。结果与低剂量GE revolution CT图像相比,应用多模型迭代重建技术重建后的肺窗和纵膈窗图像质量提高,图像噪声降低(8.83±1.95 Hu vs 9.21±2.17 Hu),信噪比升高(7.21±1.30 vs 6.89±1.22),差异均有统计学意义(P<0.05),而CT值比较差异无统计学意义(65.01±7.94 Hu vs 65.38±8.26 Hu,P>0.05)。结论多模型迭代重建技术能够提高早期肺癌低剂量GE revolution CT成像质量,对早期肺癌的筛查具有重要临床应用价值。
文摘The pyramidal multiphase level set framework （PMLSF） based on the technique of painting background （TPBG） and the Chan-Vese model can detect multiple objects on a given image. However, the boundaries of the sub-object obtained by PMLSF-TPBG are not variable since a specialcolor parameter is used in TPBG. To solve the problem, a new technique utilizing a varying parameter is proposed to ensure that PMLSF is effective for the detection of the desired boundaries of the sub-object. The interval of the variable color parameter is proved and the effects of the parameter are also discussed. Experimental results for the brain tumor detection show that different boundaries of the brain tumors can be detected with different color parameters. It is especially useful for clinical diagnoses.
基金supported by the National Basic Research Program of China(973Program)(2014CB744206)
文摘This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden.
基金Project supported by the National Natural Science Foundation of China (Nos. 60533090 and 60525108), the National Basic Research Program (973) of China (No. 2002CB312101), and the Science and Technology Project of Zhejiang Province (Nos. 2005C13032 and 2005C11001-05), China
文摘Along with the development of motion capture technique, more and more 3D motion databases become available. In this paper, a novel approach is presented for motion recognition and retrieval based on ensemble HMM (hidden Markov model) learning. Due to the high dimensionality of motion’s features, Isomap nonlinear dimension reduction is used for training data of ensemble HMM learning. For handling new motion data, Isomap is generalized based on the estimation of underlying eigen- functions. Then each action class is learned with one HMM. Since ensemble learning can effectively enhance supervised learning, ensembles of weak HMM learners are built. Experiment results showed that the approaches are effective for motion data recog- nition and retrieval.
文摘Internet multi-robotics is a typical discrete-event system. In order to describe joint activities between multiple operators and multiple robots, a 4-level discrete-event model is proposed in this paper based on the controlled condition/event Petri nets (CCEP). On the first or mission level, the task splitting of the system is defined; on the second or multi-operator level, a precedence graph is introduced for every operator to plan his or her robotic actions; on the third or coordination level, the above precedence graphs are translated and integrated into the corresponding CCEPs in terms of specific rules; and on the last or multi-robot level, operators can select their control range by setting the corresponding control marks of the obtained CCEPs. As a consequence, a clear mechanism of operator-robot collaboration is obtained to conduct the development of the system.
