Publication: Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images
Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images
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Guo, S., Lai, C., Wu, C., & Cen, G. (2017). Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images. Frontiers in Aging Neuroscience, 9, 146. https://doi.org/10.3389/fnagi.2017.00146
Abstract
Abstract
Abstract
Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the st
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- Guo, Shengwen
- Lai, Chunren
- Wu, Congling
- Cen, Guiyin
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Citations
Guo, S., Lai, C., Wu, C., & Cen, G. (2017). Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images. Frontiers in Aging Neuroscience, 9, 146. https://doi.org/10.3389/fnagi.2017.00146
