The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a subop...The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a suboptimal filter. Then, a new importance density function(IDF) was defined by the updated system equation. Particles drawn from the new IDF are more likely to be in the significant region of state space and the estimation accuracy can be improved. By using different suboptimal filter, different particle filters(PFs) can be developed in this framework. Extensions of this idea were also proposed by iteratively updating the system equation using particle filter itself, resulting in the iterated particle filter. Simulation results demonstrate the effectiveness of the proposed IDF.展开更多
Lumbar vertebra motion analysis provides objective measurement of lumbar disorder. The automatic tracking algorithm has been applied to Digitalized Video Fluoroscopy (DVF) sequence. This paper proposes a new Auto-Trac...Lumbar vertebra motion analysis provides objective measurement of lumbar disorder. The automatic tracking algorithm has been applied to Digitalized Video Fluoroscopy (DVF) sequence. This paper proposes a new Auto-Tracking System (ATS) with a guide device and a motion analysis to automatically measure human lumbar motion. Digitalized Video Fluoroscopy (DVF) sequence was obtained during flexion-extension lumbar movement under guide device. An extraction of human vertebral body and its motion tracking were developed by particle filter. The results showed a good repeatability, reliability and robustness. In model test, the maximum fiducial error is 3.7% and the repeatability error is 1.2% in translation and the maximal repeatability error is 2.6% in rotation angle. In this simulation study, we employed a lumbar model to simulate the motion of lumber flexion- extension with the stepping translation of 1.3 mm and rotation angle of 1°. Results showed that the fiducial error was measured as 1.0%, while the repeatability error was 0.7%. The sequence can be detected even noise contamination as more as 0.5 of the density. The result demonstrates that the data from the auto-tracking algorithm shows a strong correlation with the actual measurement and that the Vertebral Auto-Tracking System (VATS) is highly repetitive. In the human lumbar spine evaluation, the study not only shows the reliability of Auto-Tracking Analysis System (ATAS), but also reveals that it is robust and variable in vivo. The VATS is evaluated by the model, the simulated sequence and the human subject. It could be concluded that the developed system could provide a reliable and robust system to detect spinal motion in future medical application.展开更多
基金Project(61271296) supported by the National Natural Science Foundation of China
文摘The current measurement was exploited in a more efficient way. Firstly, the system equation was updated by introducing a correction term, which depends on the current measurement and can be obtained by running a suboptimal filter. Then, a new importance density function(IDF) was defined by the updated system equation. Particles drawn from the new IDF are more likely to be in the significant region of state space and the estimation accuracy can be improved. By using different suboptimal filter, different particle filters(PFs) can be developed in this framework. Extensions of this idea were also proposed by iteratively updating the system equation using particle filter itself, resulting in the iterated particle filter. Simulation results demonstrate the effectiveness of the proposed IDF.
文摘Lumbar vertebra motion analysis provides objective measurement of lumbar disorder. The automatic tracking algorithm has been applied to Digitalized Video Fluoroscopy (DVF) sequence. This paper proposes a new Auto-Tracking System (ATS) with a guide device and a motion analysis to automatically measure human lumbar motion. Digitalized Video Fluoroscopy (DVF) sequence was obtained during flexion-extension lumbar movement under guide device. An extraction of human vertebral body and its motion tracking were developed by particle filter. The results showed a good repeatability, reliability and robustness. In model test, the maximum fiducial error is 3.7% and the repeatability error is 1.2% in translation and the maximal repeatability error is 2.6% in rotation angle. In this simulation study, we employed a lumbar model to simulate the motion of lumber flexion- extension with the stepping translation of 1.3 mm and rotation angle of 1°. Results showed that the fiducial error was measured as 1.0%, while the repeatability error was 0.7%. The sequence can be detected even noise contamination as more as 0.5 of the density. The result demonstrates that the data from the auto-tracking algorithm shows a strong correlation with the actual measurement and that the Vertebral Auto-Tracking System (VATS) is highly repetitive. In the human lumbar spine evaluation, the study not only shows the reliability of Auto-Tracking Analysis System (ATAS), but also reveals that it is robust and variable in vivo. The VATS is evaluated by the model, the simulated sequence and the human subject. It could be concluded that the developed system could provide a reliable and robust system to detect spinal motion in future medical application.
