Neural network trigger algorithms for heavy quark event selection in a fixed target high energy physics experiment

Abstract The study of particles containing heavy quarks is currently a major topic in high energy physics. In this paper, neural net trigger algorithms are developed to distinghish heavy quark (signal) events from light quark (background) events in a fixed target experiment. The event tracks which are parametrized by the impact parameter D and the angle Φ of the track with respect to the beam line, vary in number and in position in the Φ - D plane. An invariant second-order moment feature set and an invariant D -sequence representation are derived to characterize the signal and background event track patterns in the Φ - D plane. A three-layer perceptron is trained to classify events as signal/background via the moments and D -sequences. A nearest neighbor classifier is also developed to serve as a benchmark for comparing the performance of the neural net triggers. Results indicate that the selected moment feature set and the D -sequence representation contain essential signal/background discriminatory information. The results also show that the neural network trigger algorithms are superior to the nearest neighbor trigger algorithms. A very high discrimination against background events and a very high efficiency for selecting signal events is obtained with the D -sequence neural net trigger algorithm

Investigation of a VLSI neural network chip as part of a secondary vertex trigger

Abstract An analog VLSI neural network chip (ETANN) has been trained to detect secondary vertices in simulated data for a fixed target heavy flavour production experiment. The detector response and associative memory track finding were modelled by a simulation, but the vertex detection was performed in hardware by the neural network chip and requires only a few microseconds per event. The chip correctly tags 30% of the heavy flavour events while rejecting 99% of the background, and is thus well adapted for secondary vertex triggering applications. A general purpose VME module for interfacing the ETANN to experiments, equipped with ADC/DAC circuits and a 68070 CPU, is also presented

Imaging spectroscopic performances for a Si based detection system

We present the imaging and spectroscopic capabilities of a system based on a single photon counting chip (PCC) bump-bonded on a Si pixel detector. The system measures the energy spectrum and the flux, produced by a standard mammographic tube. We have also made some images of low contrast details, achieving good results

Semiconductor pixel detectors for digital mammography

Abstract We present some results obtained with silicon and gallium arsenide pixel detectors to be applied in the field of digital mammography. Even though GaAs is suitable for medical imaging applications thanks to its atomic number, which allows a very good detection efficiency, it often contains an high concentrations of traps which decrease the charge collection efficiency (CCE). So we have analysed both electrical and spectroscopic performance of different SI GaAs diodes as a function of concentrations of dopants in the substrate, in order to find a material by which we can obtain a CCE allowing the detection of all the photons that interact in the detector. Nevertheless to be able to detect low contrast details, efficiency and CCE are not the only parameters to be optimized; also the stability of the detection system is fundamental. In the past we have worked with Si pixel detectors; even if its atomic number does not allow a good detection efficiency at standard thickness, it has a very high stability. So keeping in mind the need to increase the Silicon detection efficiency we performed simulations to study the behaviour of the electrical potential in order to find a geometry to avoid the risk of electrical breakdown

Experimental study of Compton scattering reduction in digital mammographic imaging

In mammography, the first cause of image contrast reduction arises from the photons scattered inside the examined organ. The amount of Compton scattering strongly depends on the irradiation area and on the distance between the organ and the X-ray detector. We have experimentally evaluated how these geometrical conditions affect the scattering fraction. Our experimental setup includes a single photon counting device based on a silicon pixel detector as X-ray sensor; a lucite cylinder to simulate the breast tissue, and a lead collimator to define the irradiation area. We have evaluated the contrast and the signal-to-noise ratio for images acquired in different conditions

Experimental study of Compton scattering reduction in digital mammographic imaging

In mammography, the first cause of image contrast reduction arises from the photons scattered inside the examined organ. The amount of Compton scattering strongly depends on the irradiation area and on the distance between the organ and the X-ray detector. We have experimentally evaluated how these geometrical conditions affect the scattering fraction. Our experimental setup includes a single photon counting device based on a silicon pixel detector as X-ray sensor; a lucite cylinder to simulate the breast tissue, and a lead collimator to define the irradiation area. We have evaluated the contrast and the signal-to-noise ratio for images acquired in different conditions

Study of GaAs detectors characteristics for medical imaging

In this work we present the results of a systematic study about SI GaAs detectors as a function of substrate and contact type, geometry and thickness. This study has been stimulated from the interest in using GaAs as a detector for medical imaging applications. GaAs detectors have been produced using crystals grown with different techniques and changing both the thickness (in the range 200 μm-1 mm) and the contacts type and geometry. We have measured the current-voltage characteristics and, using radioactive sources (109Cd, 20 keV photons, 241Am, 60 keV photons, 99mTc, 140 keV photons), we have studied the performance of our detectors in terms of charge collection efficiency and energy resolution as a function of the bias voltage. Besides we have also studied the electrical and spectroscopic properties of GaAs detectors with different types and concentrations of the dopants in the substrate. So we have found the optimal doping type and concentration to have the best spectroscopic performances and the higher breakdown voltage. Simulation programs made with Monte Carlo methods have been developed to describe the electric field distribution and the transport of charge carriers toward the electrodes in GaAs detectors. In these simulations we have considered the presence of deep energy levels in the bandgap, the thickness, the bias voltage and the charge deposition in the crystal after photon interaction

Low contrast imaging with a GaAs pixel digital detector

A digital mammography system based on a GaAs pixel detector has been developed by the INFN (Istituto Nazionale di Fisica Nucleare) collaboration MED46. The high atomic number makes the GaAs a very efficient material for low energy X-ray detection (10-30 keV is the typical energy range used in mammography). Low contrast details can be detected with a significant dose reduction to the patient. The system presented in this paper consists of a 4096 pixel matrix built on a 200 μm thick semi-insulating GaAs substrate. The pixel size is 170×170 μm2 for a total active area of 1.18 cm2 . The detector is bump-bonded to a VLSI front-end chip which implements a single-photon counting architecture. This feature allows to enhance the radiographic contrast detection with respect to charge integrating devices. The system has been tested by using a standard mammographic tube. Images of mammographic phantoms will be presented and compared with radiographs obtained with traditional film/screen systems. Monte Carlo simulations have been also performed to evaluate the imaging capability of the system. Comparison with simulations and experimental results will be shown

A Novel morphological approach to volume extraction in 3D tomography

Extracting a region of interest from volumetric data represents an important task in the field of digital image analysis. Several approaches to this problem are proposed in literature. The present paper affords volume extraction for regions of interest whose characteristics are not known a-priori. This is the case, for instance, of cancerous tissues in medical tomography or defects in industrial tomography. The technique here described allows extraction of completely arbitrary shapes with a minimum interaction with the user. The volume of interest is defined through the semi-automatic selection of a small set of rail contours at different planes. Such contours are then blended through a morphing technique in order to interpolate the cutting surface. The overall technique demonstrates to be intuitive, efficient and robust. Some results are reported where the method has been applied to micro-tomographic measurements

Images of soft materials: a 3D visualization of interior of the sample in terms of attenuation coefficient

Images of soft materials are obtained using image intensifier based X-ray system (Rao et al., Nucl. Instr. and Meth. A 437 (1999) 141). The interior of the soft material is visualized using the novel software in order to know the distribution of attenuation coefficient in terms of density. The novel software is based mainly on graphical library and applicable to several operating systems without any change. It can be applied to several applications starting from biomedical to industries, for example, quality control. The results for walnut and brew tooth are presented as a set of images from the internal parts of the sample. A description of the principal parameters required for tomographic visualization is given and some results based on this technique are reported and discussed