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Author  |
Llosa, G.; Barrio, J.; Cabello, J.; Crespo, A.; Lacasta, C.; Rafecas, M.; Callier, S.; de la Taille, C.; Raux, L. |
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Title |
Detector characterization and first coincidence tests of a Compton telescope based on LaBr3 crystals and SiPMs |
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Journal Article |
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Year |
2012 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
695 |
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Pages |
105-108 |
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Keywords |
Hadron therapy; Compton imaging; LaBr3; Continuous crystal; SiPM; MPPC; G-APD |
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Abstract |
A Compton telescope for dose monitoring in hadron therapy consisting of several layers of continuous LaBr3 crystals coupled to silicon photomultiplier (SiPM) arrays is under development within the ENVISION project. In order to test the possibility of employing such detectors for the telescope, a detector head consisting of a continuous 16 mm x 18 mm x 5 mm LaBr3 crystal coupled to a SiPM array has been assembled and characterized, employing the SPIROC1 ASIC as readout electronics. The best energy resolution obtained at 511 key is 6.5% FWHM and the timing resolution is 3.1 ns FWHM. A position determination method for continuous crystals is being tested, with promising results. In addition, the detector has been operated in time coincidence with a second detector layer, to determine the coincidence capabilities of the system. The first tests are satisfactory, and encourage the development of larger detectors that will compose the telescope prototype. |
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Address |
[Llosa, G.; Barrio, J.; Cabello, J.; Crespo, A.; Lacasta, C.; Rafecas, M.] UVEG, CSIC, IFIC, Inst Fis Corpuscular, Valencia, Spain, Email: gabriela.llosa@ific.uv.es |
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Elsevier Science Bv |
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English |
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ISSN |
0168-9002 |
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Notes |
WOS:000311469900020 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
1235 |
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Author |
Oliver, J.F.; Fuster-Garcia, E.; Cabello, J.; Tortajada, S.; Rafecas, M. |
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Title |
Application of Artificial Neural Network for Reducing Random Coincidences in PET |
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Journal Article |
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Year |
2013 |
Publication |
IEEE Transactions on Nuclear Science |
Abbreviated Journal |
IEEE Trans. Nucl. Sci. |
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Volume |
60 |
Issue |
5 |
Pages |
3399-3409 |
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Abstract |
Positron Emission Tomography (PET) is based on the detection in coincidence of the two photons created in a positron annihilation. In conventional PET, this coincidence identification is usually carried out through a coincidence electronic unit. An accidental coincidence occurs when two photons arising from different annihilations are classified as a coincidence. Accidental coincidences are one of the main sources of image degradation in PET. Some novel systems allow coincidences to be selected post-acquisition in software, or in real time through a digital coincidence engine in an FPGA. These approaches provide the user with extra flexibility in the sorting process and allow the application of alternative coincidence sorting procedures. In this work a novel sorting procedure based on Artificial Neural Network (ANN) techniques has been developed. It has been compared to a conventional coincidence sorting algorithm based on a time coincidence window. The data have been obtained from Monte-Carlo simulations. A small animal PET scanner has been implemented to this end. The efficiency (the ratio of correct identifications) can be selected for both methods. In one case by changing the actual value of the coincidence window used, and in the other by changing a threshold at the output of the neural network. At matched efficiencies, the ANN-based method always produces a sorted output with a smaller random fraction. In addition, two differential trends are found: the conventional method presents a maximum achievable efficiency, while the ANN-based method is able to increase the efficiency up to unity, the ideal value, at the cost of increasing the random fraction. Images reconstructed using ANN sorted data (no compensation for randoms) present better contrast, and those image features which are more affected by randoms are enhanced. For the image quality phantom used in the paper, the ANN method decreases the spill-over ratio by a factor of 18%. |
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ISSN |
0018-9499 |
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Notes |
WOS:000325827200027 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
1611 |
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