Processing CsI(Tl) 2D Matrices by means of neural network and Markov Random Fields

Alderighi, M; Anzalone, A; Baruzzi, R; Cardella, G; Cavallaro, S; De Filippo, E; Geraci, E; Giustolisi, F; Guazzoni, P; Lanzalone, Gaetano; Lanzano, G; Pagano, A; Papa, M; Pirrone, S; Politi, G; Porto Russo, S; Sambataro, S; Sechi, G; Sperduto, Ml; Zetta, L.

doi:10.1109/TNS.2002.801704

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 he 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.

Titolo:	Processing CsI(Tl) 2D Matrices by means of neural network and Markov Random Fields
Autori:	ALDERIGHI M ANZALONE A BARUZZI R CARDELLA G CAVALLARO S DE FILIPPO E GERACI E GIUSTOLISI F GUAZZONI P LANZALONE, GAETANO [Membro del Collaboration Group] (Corresponding) LANZANO G PAGANO A PAPA M PIRRONE S POLITI G PORTO RUSSO S SAMBATARO S SECHI G SPERDUTO ML ZETTA L. mostra contributor esterni nascondi contributor esterni
Data di pubblicazione:	2002
Rivista:	IEEE TRANSACTIONS ON NUCLEAR SCIENCE
Abstract:	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 he 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.
Handle:	http://hdl.handle.net/11387/7367
Appare nelle tipologie:	1.1 Articolo in rivista

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