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• W1570328450 abstract "This paper presents a unified image processing and analysis framework for cortical thickness in characterizing a clinical population. The emphasis is placed on the development of data smoothing and analysis framework. The human brain cortex is a highly convoluted surface. Due to the convoluted non-Euclidean surface geometry, data smoothing and analysis on the cortex are inherently difficult. When measurements lie on a curved surface, it is natural to assign kernel smoothing weights based on the geodesic distance along the surface rather than the Euclidean distance. We present a new data smoothing framework that address this problem implicitly without actually computing the geodesic distance and present its statistical properties. Afterwards, the statistical inference is based on the random field theory based multiple comparison correction. As an illustration, we have applied the method in detecting the regions of abnormal cortical thickness in 16 high functioning autistic children." @default.
• W1570328450 created "2016-06-24" @default.
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• W1570328450 date "2005-01-01" @default.
• W1570328450 modified "2023-10-18" @default.
• W1570328450 title "Unified Statistical Approach to Cortical Thickness Analysis" @default.
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• W1570328450 doi "https://doi.org/10.1007/11505730_52" @default.
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