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Bruno Golosio
Researcher at University of Cagliari
Publications - 146
Citations - 2741
Bruno Golosio is an academic researcher from University of Cagliari. The author has contributed to research in topics: Image resolution & Tomography. The author has an hindex of 26, co-authored 136 publications receiving 2359 citations. Previous affiliations of Bruno Golosio include University of Sassari & Istituto Nazionale di Fisica Nucleare.
Papers
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Journal ArticleDOI
The xraylib library for X-ray-matter interactions. Recent developments
Tom Schoonjans,Antonio Brunetti,Bruno Golosio,Manuel Sanchez del Rio,Vicente A. Solé,Claudio Ferrero,Laszlo Vincze +6 more
TL;DR: Xraylib as discussed by the authors is an ANSI C library that provides convenient access to a large number of X-ray related databases, with a focus on quantitative X -ray fluorescence applications.
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Internal elemental microanalysis combining x-ray fluorescence, Compton and transmission tomography
Bruno Golosio,Alexandre Simionovici,Andrea Somogyi,Laurence Lemelle,Marina Chukalina,Antonio Brunetti +5 more
TL;DR: In this paper, an approach to the reconstruction problem is presented, which integrates the information from the three types of signals, i.e., Compton and Rayleigh scattering, for obtaining information on the internal elemental composition of the sample.
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A comparative study of K-Nearest Neighbour, Support Vector Machine and Multi-Layer Perceptron for Thalassemia screening
Salvator Roberto Amendolia,Gianfranco Cossu,Maria Luisa Ganadu,Bruno Golosio,Giovanni Luca Masala,Giovanni Maria Mura +5 more
TL;DR: Both techniques enable thalassemia carriers to be discriminated from healthy subjects with 95% specificity, although the sensitivity of MLP is 92% while that of SVM is 83%.
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A library for X-ray-matter interaction cross sections for X-ray fluorescence applications
Antonio Brunetti,M. Sanchez del Rio,Bruno Golosio,Alexandre Simionovici,Alexandre Simionovici,Andrea Somogyi +5 more
TL;DR: In this paper, the authors present a compilation of data sets from different published works and an xraylib interface in the form of callable functions, which can be easily included in software applications for X-ray fluorescence.
Journal ArticleDOI
A CAD system for nodule detection in low-dose lung CTs based on region growing and a new active contour model
Roberto Bellotti,F. De Carlo,G. Gargano,Sabina Tangaro,Donato Cascio,Ezio Catanzariti,P. Cerello,Sc Cheran,Pasquale Delogu,I. De Mitri,C. Fulcheri,Daniele Grosso,Alessandra Retico,Sandro Squarcia,E. Tommasi,Bruno Golosio +15 more
TL;DR: A computer-aided detection system for the selection of lung nodules in computer tomography (CT) images is presented, based on region growing (RG) algorithms and a new active contour model (ACM), able to draw the correct contour of the lung parenchyma and to include the pleural nodules.