• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.11
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• pp.911-923
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• 2013

Multipath routing is one of challenging issues for improving the reliability of end-to-end data delivery in wireless sensor networks. Recently, a disjointedness and management of path have been studying to enhance the robustness and efficiency of the multipath routing. However, previous multipath routing protocols exploit the disjointed multipath construction method that is not to consider the wireless communication environment. In addition, if a path failures is occurred due to the node or link failures in the irregular network environment, they maintain the multipath through the simple method that to construct a new extra path. Even some of them have no a method. In order to cope with the insufficiency of path management, a hole detouring scheme, to bypass the failures area and construct the new paths, was proposed. However, it also has the problem that requires a heavy cost and a delivery suspension to the some or all paths in the hole detouring process due to the centralized and inflexible path management. Due to these limitations and problems, the previous protocols may lead to the degradation of data delivery reliability and the long delay of emergency data delivery. Thus, we propose a flexible disjoint multipath routing protocol which constructs the radio disjoint multipath by considering irregular and constrained wireless sensor networks. It also exploits a localized management based on the path priority in order to efficiently maintain the flexible disjoint multipath. We perform the simulation to evaluate the performance of the proposed method.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.12-16
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• 2012

Purpose : In conventional PET image reconstruction, iterative reconstruction methods such as OSEM (Ordered Subsets Expectation Maximization) have now generally replaced traditional analytic methods such as filtered back-projection. This includes improvements in components of the system model geometry, fully 3D scatter and low noise randoms estimates. SharpIR algorithm is to improve PET image contrast to noise by incorporating information about the PET detector response into the 3D iterative reconstruction algorithm. The aim of this study is evaluation of SharpIR reconstruction method in PET/CT. Materials and Methods: For the measurement of detector response for the spatial resolution, a capillary tube was filled with FDG and scanned at varying distances from the iso-center (5, 10, 15, 20 cm). To measure image quality for contrast recovery, the NEMA IEC body phantom (Data Spectrum Corporation, Hillsborough, NC) with diameters of 1, 13, 17 and 22 for simulating hot and 28 and 37 mm for simulating cold lesions. A solution of 5.4 kBq/mL of $^{18}F$-FDG in water was used as a radioactive background obtaining a lesion of background ratio of 4.0. Images were reconstructed with VUE point HD and VUE point HD using SharpIR reconstruction algorithm. For the clinical evaluation, a whole body FDG scan acquired and to demonstrate contrast recovery, ROIs were drawn on a metabolic hot spot and also on a uniform region of the liver. Images were reconstructed with function of varying iteration number (1~10). Results: The result of increases axial distance from iso-center, full width at half maximum (FWHM) is also increasing in VUE point HD reconstruction image. Even showed an increasing distances constant FWHM. VUE point HD with SharpIR than VUE point HD showed improves contrast recovery in phantom and clinical study. Conclusion: By incorporating more information about the detector system response, the SharpIR algorithm improves the accuracy of underlying model used in VUE point HD. SharpIR algorithm improve spatial resolution for a line source in air, and improves contrast recovery at equivalent noise levels in phantoms and clinical studies. Therefore, SharpIR algorithm can be applied as through a longitudinal study will be useful in clinical.