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Processing CsI(Tl) 2-D matrices by means of neural networks and Markov random fields

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19 Author(s)
M. Alderighi ; Ist. di Fisica Cosmica e Tecnologie Relative, CNR, Milan ; A. Anzalone ; R. Baruzzi ; G. Cardella
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This paper is concerned with the automatic analysis of data coming from the multidetector array CHIMERA, used in nuclear physics at intermediate energies. Each of Chimera's detection cells is a telescope made of a ΔE silicon detector and a CsI(Tl) crystal, thick enough to stop all the charged light particles. The signals produced in the CsI(Tl) scintillators can be subdivided into two components-fast and slow. These data are collected in the form of bi-dimensional matrices (Fast-Slow matrices), particularly important for light particle identification. The proposed approach consists in applying image processing techniques. In particular, Grossberg's pre-attentive neural networks are used as a first step in order to isolate the regions of physical interest in the matrices and to roughly identify the directions depicted by the most intense lines; a successive step of filtering based on Markov random fields is then performed.

Published in:

IEEE Transactions on Nuclear Science  (Volume:49 ,  Issue: 4 )