Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the probl...Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the problem of 3D target tracking with strong maneuverability, on the basis of the modified three-dimensional variable turn (3DVT) model, an adaptive tracking algorithm is proposed by combining with the cubature Kalman filter (CKF) in this paper. Through ideology of real-time identification, the parameters of the model are changed to adjust the state transition matrix and the state noise covariance matrix. Therefore, states of the target are matched in real-time to achieve the purpose of adaptive tracking. Finally, four simulations are analyzed in different settings by the Monte Carlo method. All results show that the proposed algorithm can update parameters of the model and identify motion characteristics in real-time when targets tracking also has a better tracking accuracy.展开更多
文摘目的 研究三维可视化技术(three-dimensional visualization technology,3DVT)在肝切除联合胆道镜探查取石术治疗肝内胆管结石的应用效果。方法 回顾性分析2018年1月至2020年12月南华大学附属第一医院肝胆胰外科收治的132例肝内胆管结石患者的临床资料,根据术前是否采用3DVT指导分为试验组(n=74)和对照组(n=58),比较两组结石清除的疗效。结果 与对照组比,试验组具有较短的术后住院时间[(15.1±6.9)d vs (19.6±10.9)d,P=0.01]、较高的结石清除率(94.59% vs 82.76%,P=0.028)及较低的结石复发率(6.76% vs 18.97%,P=0.033)。结论 3DVT引导肝切除联合胆道镜探查取石术治疗肝内胆管结石是可行的,对有效清除肝内结石具有较大的优势。
基金supported by the National Natural Science Foundation of China(51467013)
文摘Satisfactory results cannot be obtained when three-dimensional (3D) targets with complex maneuvering characteristics are tracked by the commonly used two-dimensional coordinated turn (2DCT) model. To address the problem of 3D target tracking with strong maneuverability, on the basis of the modified three-dimensional variable turn (3DVT) model, an adaptive tracking algorithm is proposed by combining with the cubature Kalman filter (CKF) in this paper. Through ideology of real-time identification, the parameters of the model are changed to adjust the state transition matrix and the state noise covariance matrix. Therefore, states of the target are matched in real-time to achieve the purpose of adaptive tracking. Finally, four simulations are analyzed in different settings by the Monte Carlo method. All results show that the proposed algorithm can update parameters of the model and identify motion characteristics in real-time when targets tracking also has a better tracking accuracy.