• Progress in Medical Physics
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• v.26 no.1
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• pp.18-27
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• 2015

Since a Compton camera has high detection sensitivity due to electronic collimation and a good energy resolution, it is a potential imaging system for nuclear medicine. In this study, we investigated the feasibility of a Compton camera for multi-tracer imaging and proposed a rotating Compton camera to satisfy Orlov's condition for 3D imaging. Two software phantoms of 140 and 511 keV radiation sources were used for Monte-Carlo simulation and then the simulation data were reconstructed by listmode ordered subset expectation maximization to evaluate the capability of multi-tracer imaging in a Compton camera. And the Compton camera rotating around the object was proposed and tested with different rotation angle steps for improving the limited coverage of the fixed conventional Compton camera over the field-of-view in terms of histogram of angles in spherical coordinates. The simulation data showed the separate 140 and 511 keV images from simultaneous multi-tracer detection in both 2D and 3D imaging and the number of valid projection lines on the conical surfaces was inversely proportional to the decrease of rotation angle. Considering computation load and proper number of projection lines on the conical surface, the rotation angle of 30 degree was sufficient for 3D imaging of the Compton camera in terms of 26 min of computation time and 5 million of detected event number and the increased detection time can be solved with multiple Compton camera system. The Compton camera proposed in this study can be effective system for multi-tracer imaging and is a potential system for development of various disease diagnosis and therapy approaches.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1802-1808
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• 2003

In this paper, we propose a method about the extraction of the pedestrian tracking trajectory in the road and we used the method of mosaic background extraction and adaptive neural network for automatic pedestrian tracking system. We used mosaic background extraction to overcome ghost phenomenon. And we detected pedestrian using differential image analysis. We used adaptive neural network for multiple pedestrian tracking that non­rigid form moving. The ART2 network is capable of detecting the mass­centers of moving objects within one frame. The history of neurons positions in the sequential frames approximates the traces of the targets. The experiments done with the network in simulated environment show promising results.