Attenuation correction is an essential requirement for quantification of positron emission tomography (PET) data. In PET/CT acquisition systems, attenuation maps are derived from computed tomography (CT) images. However, in hybrid PET/MR scanners, magnetic resonance imaging (MRI) images do not directly provide a patient-specific attenuation map. The aim of the proposed work is to improve attenuation correction for PET/MR scanners by generating synthetic CTs and attenuation maps. The synthetic images are generated through a multi-atlas information propagation scheme, locally matching the MRI-derived patient's morphology to a database of MRI/CT pairs, using a local image similarity measure. Results show significant improvements in CT synthesis and PET reconstruction accuracy when compared to a segmentation method using an ultrashort-echo-time MRI sequence and to a simplified atlas-based method.

The fundamental challenge for designing transparent conductors used in photovoltaics, displays and solid-state lighting is the ideal combination of high optical transparency and high electrical conductivity. Satisfying these competing demands is commonly achieved by increasing carrier concentration in a wide-bandgap semiconductor with low effective carrier mass through heavy doping, as in the case of tin-doped indium oxide (ITO). Here, an alternative design strategy for identifying high-conductivity, high-transparency metals is proposed, which relies on strong electron-electron interactions resulting in an enhancement in the carrier effective mass. This approach is experimentally verified using the correlated metals SrVO3 and CaVO3, which, despite their high carrier concentration (>2.2 × 10(22) cm(-3)), have low screened plasma energies (<1.33 eV), and demonstrate excellent performance when benchmarked against ITO. A method is outlined to rapidly identify other candidates among correlated metals, and strategies are proposed to further enhance their performance, thereby opening up new avenues to develop transparent conductors.

A growing body of preclinical evidence indicates that addiction to cocaine is associated with neuroadaptive changes in frontostriatal brain systems. Human studies in cocaine-dependent individuals have shown alterations in brain structure, but it is less clear how these changes may be related to the clinical phenotype of cocaine dependence characterized by impulsive behaviours and compulsive drug-taking. Here we compared self-report, behavioural and structural magnetic resonance imaging data on a relatively large sample of cocaine-dependent individuals (n = 60) with data on healthy volunteers (n = 60); and we investigated the relationships between grey matter volume variation, duration of cocaine use, and measures of impulsivity and compulsivity in the cocaine-dependent group. Cocaine dependence was associated with an extensive system of abnormally decreased grey matter volume in orbitofrontal, cingulate, insular, temporoparietal and cerebellar cortex, and with a more localized increase in grey matter volume in the basal ganglia. Greater duration of cocaine dependence was correlated with greater grey matter volume reduction in orbitofrontal, cingulate and insular cortex. Greater impairment of attentional control was associated with reduced volume in insular cortex and increased volume of caudate nucleus. Greater compulsivity of drug use was associated with reduced volume in orbitofrontal cortex. Cocaine-dependent individuals had abnormal structure of corticostriatal systems, and variability in the extent of anatomical changes in orbitofrontal, insular and striatal structures was related to individual differences in duration of dependence, inattention and compulsivity of cocaine consumption.

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