1,721,030 research outputs found
Brain morphometry in autism spectrum disorders: a unified approach for structure-specific statistical analysis of neuroimaging data - biomed 2011.
No full textAutism spectrum disorders (ASD) are a neurodevelopmental condition with multiple causes, comorbid conditions, and a wide range in the type and severity of symptoms expressed by different individuals. This makes the neuroanatomy of autism inherently difficult to describe. It has been assumed in the scientific literature that deviations in regional brain size in clinical samples are directly related to maldevelopment or pathogenesis. The performed clinical studies analyzed specific brain structures that are assumed to be correlated to autistic brain behaviors. Examples of performed analyses, based upon manual or semi-automated segmentation from magnetic resonance imaging (MRI) scans, include volumetric measures of specific brain structures, or small groups of structures, as caudate, corpus callosum, putamen, hippocampus, nucleus accumbens, evaluating differences between groups of subjects with autism and control subjects. Nonetheless, the brain regions analyzed that differ between patients and control subjects have not been always consistent over the performed studies. This inconsistency might be due to the fact that the specific single volume differences that have been reported in the literature for the different brain structures under investigation may, instead, be not independent during pathogenesis. Hence, this issue comes into play in logically framing a comprehensive assessment of putative abnormalities in regional brain volumes. To this aim, a whole brain investigation system for a semi-automated morphometric statistical analysis of brain anatomy is presented in this paper and validated on a selected group of patients diagnosed with ASD that completed a 1.5 T magnetic resonance image (MRI) of the brain. The proposed system, which is mainly built basing upon the FreeSurfer and the 3D Slicer software frameworks for the volumetric analysis of brain imaging data, lies its foundations on the higher statistical power of the region of interest (ROI) approach, but equally aims at a higher exploratory power as it doesn t restrict its focus to a small number of specific regions, thanks to a whole brain unified approach
Performance enhancement of partially systematic rate-compatible SCCCs through puncturing design
No full textartially systematic rate-compatible serial concatenated convolutional codes (SCCCs) are considered. These are generated from a classical rate 1/3 serial concatenated mother code. To obtain rate-compatible SCCCs, the puncturing is limited to inner coded bits, by puncturing both the inner code's parity and systematic bits. It is shown that the performance can be enhanced in the "waterfall" or in the "error-floor" region, by simply spreading the puncturing over the parity and the systematic bits without increasing encoding and decoding complexity
Performance bounds of continuous and blockwise decoded turbo codes in Rician fading channel
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Turbo Codes Performance Optimization Over Block Fading Channels
No full textIn this paper, the best achievable performance of a turbo coded system on a block fading channel is obtained. The block fading channel model is motivated by the fact that in many wireless systems the coherence time of the channel is much longer than one symbol interval, resulting in adjacent symbols being affected by the same fading value. The fading blocks will experience independent fades, assuming a sufficient separation in time, in frequency, or both in time and in frequency. This channel model is suitable for analyzing, for instance, wireless communication systems employing techniques such as slow frequency-hopping, as is done in the Global System for Mobile communications (GSM). In such systems, coded information is transmitted over a small number of fading channels in order to achieve diversity. The best coded information allocations over a certain number of fading channels are evaluated, using the Eades-McKay algorithm to generate distinct permutations of a multiset. Bounds on the achievable performance due to coding are derived using information-theoretic techniques. In particular, in the paper an analytical method is proposed, based on the sphere-packing bounding technique, to assess the achievable performance. Moreover, simulation results are obtained and compared with the theoretical one
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