Volume properties of the hippocampal regions as predictors of DAT development

In this work we look at the statistical distribution of geometrical observables computed in volumes centered on the right and left hippocampus in MR images. The observable distributions are then correlated with the clinical diagnosis in patients potentially affected by the Alzheimer disease. We then evaluate the discrimination ability of the geometrical observables combined with the MMSE test results

Automatic localization of the hippocampal region in MR images to asses early diagnosis of Alzheimer’s Disease in MCI patients

A trophy and other brain changes, which are typical of aging, generate wide inter-individual variability of morphology in the medial temporal lobe (MTL), including the hippocampal formation. Starting from a sample population of 133 MR images we developed a procedure that extracts from each MR two sub images, containing the hippocampal formations plus a portion of the adjacent tissues and cavities. Then, a small number of templates is selected among the previously obtained sub images, able to describe the morphological variability present in the whole population. Finally an automatic procedure is prepared which, on the basis of the given set of templates, is able to find both hippocampal formations in any new MR image. MR images ranging from normalcy to extreme atrophy can be successfully processed. The proposed approach, besides being a preliminary step towards the unsupervised segmentation of the hippocampus, extracts from the MR image information useful for diagnostic purposes and, in particular, could give the possibility of performing morphometric studies on the media] temporal lobe in an automated way. The automated analysis of MTL atrophy in the segmented volume is readily applied to the early assessment of Alzheimer Disease (AD), leading to discriminating converters from Mild Cognitive Impairment (MCI) to AD with an average three years follow-up. This procedure can quickly and reliably provide additional information in early diagnosis of AD

Application of muon tomography to detect radioactive sources hidden in scrap metal containers2013 3rd International Conference on Advancements in Nuclear Instrumentation, Measurement Methods and their Applications (ANIMMA)

none13The accidental melting of radioactive sources hidden inside metal scrap containers can produce severe environmental harm. Modern melting facilities are equipped with portals measuring radiation levels. Nonetheless, sources can pass undiscovered when shielded inside shells of high density material, such as lead. From time to time indeed some radioactive sources pass undetected through the controls at foundries entrance. Once melted they caused enormous damages to the steel mills, contaminating all the production line. The muon tomography technique allows to discriminate high- Z materials measuring multiple scattering of cosmic ray muons inside matter. Therefore this technique can be used to analyze a truck container searching for high-density source shields. We report here the results about simulation studies of a muon tomography portal. Within the Mu-Steel European project we developed the prototype design, the three-dimensional images reconstruction software and the high density material identification algorithm. MonteCarlo simulation was validated with data from a large volume demonstrator (~11 m3) built using spare muon drift-time chambers of the CMS high energy physics experiment operating at the Large Hadron Collider at CERN.noneMatteo Furlan;Andrea Rigoni;Sara Vanini;Gianni Zumerle;Paolo Checchia;Ludovico Cossutta;Giacomo Bettella;Pietro Zanuttigh;Piero Calvini;Luca Dassa;Antonietta Donzella;Germano Bonomi;Aldo ZenoniFurlan, Matteo; RIGONI GAROLA, Andrea; Vanini, Sara; Zumerle, Gianni; Checchia, Paolo; Ludovico, Cossutta; Bettella, Giacomo; Zanuttigh, Pietro; Piero, Calvini; Luca, Dassa; Antonietta, Donzella; Germano, Bonomi; Aldo, Zenon

Application of Muon Tomography to Detect Radioactive Sources Hidden in Scrap Metal Containers

The accidental melting of radioactive sources hidden inside metal scrap containers can produce severe environmental harm. Modern melting facilities are equipped with portals measuring radiation levels. Nonetheless, sources can pass undiscovered when shielded inside shells of high density material, such as lead. From time to time indeed some radioactive sources pass undetected through the controls at foundries entrance. Once molten they caused enormous damages to the steel mills, contaminating all the production line. The muon tomography technique allows to discriminate high-Z materials measuring multiple scattering of cosmic ray muons inside matter. Therefore this technique can be used to analyse a truck container searching for high-density source shields. We report here the results about simulation studies of a muon tomography portal. Within the Mu-Steel European project we developed the prototype design, the three-dimensional images reconstruction software and the high density material identification algorithm. MonteCarlo simulation was validated with data from a large volume demonstrator (similar to 11 m(3)) built using spare muon drift-time chambers of the CMS high energy physics experiment operating at the Large Hadron Collider at CERN.The accidental melting of radioactive sources hidden inside metal scrap containers can produce severe environmental harm. Modern melting facilities are equipped with portals measuring radiation levels. Nonetheless, sources can pass undiscovered when shielded inside shells of high density material, such as lead. From time to time indeed some radioactive sources pass undetected through the controls at foundries entrance. Once molten they caused enormous damages to the steel mills, contaminating all the production line. The muon tomography technique allows to discriminate high-Z materials measuring multiple scattering of cosmic ray muons inside matter. Therefore this technique can be used to analyse a truck container searching for high-density source shields. We report here the results about simulation studies of a muon tomography portal. Within the Mu-Steel European project we developed the prototype design, the three-dimensional images reconstruction software and the high density material identification algorithm. MonteCarlo simulation was validated with data from a large volume demonstrator (similar to 11 m(3)) built using spare muon drift-time chambers of the CMS high energy physics experiment operating at the Large Hadron Collider at CERN

Application of Muon Tomography to Detect Radioactive Sources Hidden in Scrap Metal Containers

The accidental melting of radioactive sources hidden inside metal scrap containers can produce severe environmental harm. Modern melting facilities are equipped with portals measuring radiation levels. Nonetheless, sources can pass undiscovered when shielded inside shells of high density material, such as lead. From time to time indeed some radioactive sources pass undetected through the controls at foundries entrance. Once molten they caused enormous damages to the steel mills, contaminating all the production line. The muon tomography technique allows to discriminate high-Z materials measuring multiple scattering of cosmic ray muons inside matter. Therefore this technique can be used to analyse a truck container searching for high-density source shields. We report here the results about simulation studies of a muon tomography portal. Within the Mu-Steel European project we developed the prototype design, the three-dimensional images reconstruction software and the high density material identification algorithm. MonteCarlo simulation was validated with data from a large volume demonstrator (~11 m3) built using spare muon drift-time chambers of the CMS high energy physics experiment operating at the Large Hadron Collider at CERN