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21 results on '"Raso, G."'

6. Mammogram Segmentation by Contour Searching and Mass Lesions Classification With Neural Network

Author

Cascio, D., Fauci, F., Magro, R., Raso, G., Bellotti, R., De Carlo, F., Tangaro, S., De Nunzio, G., Quarta, M., Forni, G., Lauria, A., Fantacci, M.E., Retico, A., Masala, Giovanni Luca, Oliva, P., Bagnasco, S., Cheran, S.C., Torres, E.L., Cascio, D., Fauci, F., Magro, R., Raso, G., Bellotti, R., De Carlo, F., Tangaro, S., De Nunzio, G., Quarta, M., Forni, G., Lauria, A., Fantacci, M.E., Retico, A., Masala, Giovanni Luca, Oliva, P., Bagnasco, S., Cheran, S.C., and Torres, E.L.

Abstract

The mammography is the most effective procedure for an early diagnosis of the breast cancer. In this paper, an algorithm for detecting masses in mammographic images will be presented. The database consists of 3762 digital images acquired in several hospitals belonging to the MAGIC-5 collaboration (Medical Applications on a Grid Infrastructure Connection). A reduction of the whole image's area under investigation is achieved through a segmentation process, by means of a ROI Hunter algorithm, without loss of meaningful information. In the following classification step, feature extraction plays a fundamental role: some features give geometrical information, other ones provide shape parameters. Once the features are computed for each ROI, they are used as inputs to a supervised neural network with momentum. The output neuron provides the probability that the ROI is pathological or not. Results are provided in terms of ROC and FROC curves: the area under the ROC curve was found to be A Z =0.862plusmn0.007, and we get a 2.8 FP/Image at a sensitivity of 82%. This software is included in the CAD station actually working in the hospitals belonging to the MAGIC-5 Collaboration

Published
2006

14. A 50 Microns Granularity Monolithic Ge Target.

Author

Amendolia, S. R., Bedeschi, F., Bertolucci, E., Bettoni, D., Bosisio, L., Bottigli, U., Bradaschia, C., Dell'Orso, M., Fidecaro, F., Foa', L., Focardi, E., Giannetti, P., Giorgi, M. A., Marrocchesi, P. S., Menzione, A., Raso, G., Ristori, L., Scribano, A., Stefanini, A., and Tenchini, R.

Published
1984
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16. The MAGIC-5 project: medical applications on a grid infrastructure connection

Author

Bellotti, R., primary, Bagnasco, S., additional, Bottigli, U., additional, Castellano, M., additional, Cataldo, R., additional, Catanzariti, E., additional, Cerello, P., additional, Cheran, S.C., additional, De Carlo, F., additional, Delogu, P., additional, De Mitri, I., additional, De Nunzio, G., additional, Fantacci, M.E., additional, Fauci, F., additional, Forni, G., additional, Gargano, G., additional, Golosio, B., additional, Indovina, P.L., additional, Lauria, A., additional, Lopez Torres, E., additional, Magro, R., additional, Martello, D., additional, Masala, G.L., additional, Massafra, R., additional, Oliva, P., additional, Palmiero, R., additional, Martinez, A.P., additional, Prevete, R., additional, Quarta, M., additional, Ramello, L., additional, Raso, G., additional, Retico, A., additional, Santoro, M., additional, Sitta, M., additional, Stumbo, S., additional, Tangaro, S., additional, Tata, A., additional, and Zanon, E., additional

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17. Mammogram segmentation by contour searching and massive lesion classification with neural network

Author

Fauci, F., primary, Bagnasco, S., additional, Bellotti, R., additional, Cascio, D., additional, Cheran, S.C., additional, De Carlo, F., additional, De Nunzio, G., additional, Fantacci, M.E., additional, Forni, G., additional, Lauria, A., additional, Lopez Torres, E., additional, Magro, R., additional, Masala, G.L., additional, Oliva, P., additional, Quarta, M., additional, Raso, G., additional, Retico, A., additional, and Tangaro, S., additional

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18. The 'Livio Scarsi' X-Ray Facility at University of Palermo for Device Testing

Author

M. Quartararo, Gaetano Gerardi, Giuseppe Raso, A.A. Turturici, Leonardo Abbene, Fabio Principato, Francesco Pintacuda, Principato, F., Gerardi, G., Turturici, A. A., Raso, G., Quartararo, M., Pintacuda, F., and Abbene, L.

Subjects
Engineering, Photon, business.industry, Settore FIS/01 - Fisica Sperimentale, X-ray, Gamma ray, Semiconductor device, Fluence, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin), Semiconductor detector, X-ray facility, semiconductor detectors, digital pulse processing, rad-hard MOSFETs, total ionizing tests, Optics, Absorbed dose, Irradiation, business, Telecommunications
Abstract

In this work, we report on the characteristics of the Livio Scarsi X-ray facility at University of Palermo. The facility is able to produce low energy X rays, within the energy range of 0.1-60 keV, with fluence rates ranging from 105-108 photons/mm2 s. The laboratory is equipped with an innovative digital detection system, based on semiconductor detectors (Si and CdTe detectors), able to provide accurate and precise estimation of the fluence rate, the energy and the exposure of X rays, even at high counting rate conditions. Instrumentation for electrical characterization (DC-AC) of semiconductor devices, for both off-line and on-line (i.e. during the irradiation) measurements, is also available. Total ionizing dose (TID) tests on rad-hard power MOSFET transistors by using both X rays and 60Co gamma rays are presented. The aim of this work is to open up to potential users for low energy X-ray applications.

Published
2015

19. Characterization of Al-Schottky CdTe detectors

Author

S. Del Sordo, Giuseppe Raso, Leonardo Abbene, Fabio Principato, A.A. Turturici, Gaetano Gerardi, Abbene, L, Gerardi, G, Principato, F, Turturici, A A, Del Sordo, S, and Raso, G

Subjects
Physics, X-ray spectroscopy, Spectrometer, business.industry, Settore FIS/01 - Fisica Sperimentale, Detector, Schottky diode, Biasing, Settore FIS/07 - Fisica Applicata(Beni Culturali, Ambientali, Biol.e Medicin), Anode, CdTe detector, Full width at half maximum, X-ray and gamma ray spectroscopy, Optics, Optoelectronics, Gamma spectroscopy, business
Abstract

In the last decades, great efforts are being devoted to the development of CdTe detectors for high resolution X-ray and gamma ray spectroscopy. Recently, new rectifying contacts based on aluminum (Al) are very appealing in the development of CdTe detectors with low leakage currents and anode pixellization. In this work, we report on preliminary results of electrical and spectroscopic investigations on Schottky CdTe diode detectors (4.1 × 4.1 × 0.75 and 4.1 × 4.1 × 2 mm3) with Au/Ti/Al/CdTe/Pt electrode configuration. The detectors are characterized by very low leakage currents even at room temperature (26 pA at 25 °C under a bias voltage of −100 V for the 2 mm thick detector). Polarization phenomena, typical of CdTe diode detectors, were investigated through electrical and spectroscopic approaches, pointing out the influence of the bias voltage, the temperature and the detector thickness. Good time stability, during a short-term operation of one hour, was observed for both detectors at temperatures below 10 °C and by using an electric field of 5000 V/cm. The detectors exhibited good energy resolution of 1.5 keV (FWHM) at 59.5 keV (T=−25 °C) by using a standard electronic chain. This work was carried out in the framework of the development of portable X-ray spectrometers for both laboratory research and medical applications.

Published
2011

20. A method to reduce the FP/imm number through CC and MLO views comparison in mammographic images

Author

R. Magro, Giuseppe Raso, M. Vasile, R. Ienzi, Francesco Fauci, Liliana Lo Presti, M. Iacomi, Donato Cascio, Salvatore Sorce, M. Glorioso, MAGRO R, CASCIO D, FAUCI F, LO PRESTI L, RASO G, IENZI R, GLORIOSO M, IACOMI M, VASILE M S, and SORCE S

Subjects
Breast tissue, Data set, business.industry, Pathological image, Geometric transformation, Pattern recognition, Symmetry properties, Reduction (complexity), Correlation, Medical imaging, Medicine, Artificial intelligence, Nuclear medicine, business, Image resolution, Transformation geometry, Mammographic, Mammographic image
Abstract

In this paper we propose a method to reduce the FP/imm number through CC and MLO mammographic views comparison of the same patient. The proposed solution uses the symmetry properties of the breast to compute a geometric transformation that permits to represent the two images in comparable coordinates systems. Through this method, potential pathological ROIs of one of the projections are correlated with the ROIs in the second view. To show the effectiveness of the result we apply the method on a dataset composed of 112 couples of pathological images. Experiments shows that method enables a reduction by up to 700/0 of the FP/imm number detected after the classification step

Published
2008

21. A fourier-based algorithm for micro-calcification enhancement in mammographic images

Author

M. Iacomi, Donato Cascio, Giuseppe Raso, R. Magro, A. La Manna, M. Vasile, Francesco Fauci, FAUCI F, LA MANNA A, CASCIO D, MAGRO R, RASO G, IACOMI M, and VASILE M S

Subjects
medicine.diagnostic_test, Computer science, Microcalcifications, Cancer, Microcalcification, medicine.disease, Fourier, symbols.namesake, Fourier transform, Breast cancer, Image preprocessing, Breast Cancer, medicine, Medical imaging, symbols, Mammography, Hard task, CAD system, Algorithm, Mammographic, Mammographic image, Calcification
Abstract

Breast cancer is the most widespread cancer in women in the world; it manifests mostly in two forms: microcalcifications and massive lesions. These two forms differ in density, size, shape and number. Consequently, there are two different kinds of mammographic CAD algorithms: those for microcalcifications detection, and those for massive lesions detection. The microcalcifications detection is a hard task, since they are quite small and often poorly contrasted against the background, especially in images affected by digitization noise. In a CAD system the ROI Hunter plays an important role, because missed microcalcifications at this level are definitely lost. For this reason, highlighting methods for suspected microcalcifications may be useful in a CAD system. In this work, we describe a Fourier Transform based microcalcifications enhancement method, which takes place after the image preprocessing and before the ROI Hunter step, aimed at highlighting suspected areas

Published
2008

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