Giuseppe Raso

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The inclusive production of the ω(782) vector meson in hadronic Z decays is measured and compared to model predictions. The analysis is based on 4 million hadronic Z decays recorded by the ALEPH detector between 1991 and 1995. The production rate for x p = p meson /p beam > 0.05 is measured in the ω → π + π − π 0 decay mode and found to be 0.585 ± 0.019(More)
We propose a computer-aided detection (CAD) system which can detect small-sized (from 3mm) pulmonary nodules in spiral CT scans. A pulmonary nodule is a small lesion in the lungs, round-shaped (parenchymal nodule) or worm-shaped (juxtapleural nodule). Both kinds of lesions have a radio-density greater than lung parenchyma, thus appearing white on the(More)
The full LEP-1 data set collected with the ALEPH detector at the Z pole during 1991-1995 is analysed in order to measure the τ decay branching fractions. The analysis follows the global method used in the published study based on 1991-1993 data, but several improvements are introduced, especially concerning the treatment of photons and π 0 's. Extensive(More)
Mass localization plays a crucial role in computer-aided detection (CAD) systems for the classification of suspicious regions in mammograms. In this article we present a completely automated classification system for the detection of masses in digitized mammographic images. The tool system we discuss consists in three processing levels: (a) Image(More)
The GPCALMA (Grid Platform for Computer Assisted Library for MAmmography) collaboration involves several departments of physics, INFN (National Institute of Nuclear Physics) sections, and italian hospitals. The aim of this collaboration is developing a tool that can help radiologists in early detection of breast cancer. GPCALMA has built a large distributed(More)
A new algorithm for massive lesion detection in mammography is presented. The algorithm consists in three main steps: 1) reduction of the dimension of the image to be processed through the identification of regions of interest (roi) as candidates for massive lesions; 2) characterization of the RoI by means of suitable feature extraction; 3) pattern(More)
BACKGROUND This work investigates the applicability of a novel clustering approach to the segmentation of mammographic digital images. The chaotic map clustering algorithm is used to group together similar subsets of image pixels resulting in a medically meaningful partition of the mammography. METHODS The image is divided into pixels subsets(More)
BACKGROUND Mammography has established itself as the most efficient technique for the identification of the pathological breast lesions. Among the various types of lesions, microcalcifications are the most difficult to identify since they are quite small (0.1-1.0 mm) and often poorly contrasted against an images background. Within this context, the Computer(More)
Purpose of this work is the development of an automatic classification system which could be useful for radiologists in the investigation of breast cancer. The software has been designed in the framework of the MAGIC-5 collaboration. In the traditional way of learning from examples of objects the classifiers are built in a feature space. However, an(More)
The triple gauge-boson couplings involving the W are determined using data samples collected with the ALEPH detector at mean centre-of-mass energies of 183 GeV and 189 GeV, corresponding to integrated luminosities of 57 pb −1 and 174 pb −1 , respectively. The couplings, g Z 1 , κ γ and λ γ , are measured using W-pair events, single-W production and single-γ(More)