Visualizing the evolution of abnormal metabolic networks in the brain using pet
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摘要
By applying novel statistical methods and visualization techniques to PET data obtained from combined groups of patients and normals, we are able to illustrate topographic covariance profiles unique to neurodegenerative disorders such as Parkinson's Disease at various stages of progression. Each profile represents a neuroanatomical network of metabolically covarying regions. The expression of the profile in each patient is characterized by a subject score which can correlate with independent clinical disease severity measures. To visualize these profiles, a semi-automatic routine is used which creates a three-dimensional (3D) animation of the metabolic topography as it evolves from initial to final stages of the disease.

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