0000000000677113

AUTHOR

P Cerello

showing 3 related works from this author

Distributed medical images analysis on a Grid infrastructure

2007

In this paper medical applications on a Grid infrastructure, the MAGIC-5 Project, are presented and discussed. MAGIC-5 aims at developing Computer Aided Detection (CADe) software for the analysis of medical images on distributed databases by means of GRID Services. The use of automated systems for analyzing medical images improves radiologists’ performance; in addition, it could be of paramount importance in screening programs, due to the huge amount of data to check and the cost of related manpower. The need for acquiring and analyzing data stored in different locations requires the use of Grid Services for the management of distributed computing resources and data. Grid technologies allow…

GRID; Virtual Organization; Medical ApplicationsComputer Networks and CommunicationsComputer scienceVirtual organizationmammographyComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONcomputer.software_genreGRID; virtual organization; CAD; mammography; medical applicationsSoftwareComputer aided diagnosimedicineMammographyCADComputer visionGridLung tumorDistributed databasemedicine.diagnostic_testmedical applicationsbusiness.industryDigital imagingGridDigital imagingHardware and ArchitectureImage analysiArtificial intelligenceData miningAlzheimer diseasevirtual organizationGRIDbusinesscomputerSoftwareMammography
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ALICE: Physics performance report, volume II

2006

ALICE is a general-purpose heavy-ion experiment designed to study the physics of strongly interacting matter and the quark-gluon plasma in nucleus-nucleus collisions at the LHC. It currently involves more than 900 physicists and senior engineers, from both the nuclear and high-energy physics sectors, from over 90 institutions in about 30 countries. The ALICE detector is designed to cope with the highest particle multiplicities above those anticipated for Pb-Pb collisions (dN(ch)/dy up to 8000) and it will be operational at the start-up of the LHC. In addition to heavy systems, the ALICE Collaboration will study collisions of lower-mass ions, which are a means of varying the energy density, …

PhysicsParticle physicsNuclear and High Energy PhysicsLarge Hadron Collider010308 nuclear & particles physicsPhysicsDetectorMonte Carlo methodObservable7. Clean energy01 natural sciencesParticle identificationNuclear physics0103 physical sciencesALICE (propellant)010306 general physicsNuclear ExperimentALICE; physics; performance; detector; CERN; QGP; LHCEvent (particle physics)Event reconstruction
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A completely automated CAD system for mass detection in a large mammographic database.

2006

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 segmentation for the localization of regions of interest (ROIs). This step relies on an iterative dynamical threshold algorithm able to select iso-intensity closed contours around gray level maxima of the mammogram. (b) ROI characterization by means of textural features computed from the gray tone spatial dependence matrix (GTSDM), containing secon…

Databases FactualInformation Storage and RetrievalReproducibility of ResultsBreast NeoplasmsSensitivity and SpecificityNeural networkPattern Recognition AutomatedRadiographic Image EnhancementBreast cancerTextural featuresRadiology Information SystemsImage processingComputer-aided detection (CAD)Artificial IntelligenceCluster AnalysisDatabase Management SystemsHumansRadiographic Image Interpretation Computer-AssistedFemaleBreast cancer; Computer-aided detection (CAD); Image processing; Mammographic mass detection; Neural network; Textural featuresMammographic mass detectionAlgorithmsMammographyMedical physics
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