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• W2437571189 abstract "Autism Spectrum Disorder (ASD) has been suggested to associate with alterations in brain connectivity. In this study, we focus on a fiber clustering tractography segmentation strategy to observe white matter connectivity alterations in ASD. Compared to another popular parcellation-based approach for tractography segmentation based on cortical regions, we hypothesized that the clustering-based method could provide a more anatomically correspondent division of white matter. We applied this strategy to conduct a population-based group statistical analysis for the automated prediction of ASD. We obtained a maximum classification accuracy of 81.33% between ASDs and controls, compared to the results of 78.00% from the parcellation-based method." @default.
• W2437571189 created "2016-06-24" @default.
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• W2437571189 date "2016-04-01" @default.
• W2437571189 modified "2023-09-22" @default.
• W2437571189 title "Fiber clustering based white matter connectivity analysis for prediction of Autism Spectrum Disorder using diffusion tensor imaging" @default.
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• W2437571189 doi "https://doi.org/10.1109/isbi.2016.7493331" @default.
• W2437571189 hasPublicationYear "2016" @default.
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