Use of population-specific atlases for brain morphometry: benefits in Alzheimer’s Disease diagnosis decision support for Chinese patients
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AbstractMCI (Mild Cognitive Impairment) is a pre-stage of Alzheimer’s Disease (AD). And the early detection of MCI is important for early treatment of AD patients. In this work, prediction efficiency of early stage of AD based on the functional connectivity network characteristics was evaluated by using a couple of classifiers with AAL_90 and AAL_1024 templates. The results showed that brain functional characteristics were effective in the prediction of MCI with a SVM-based classifier. And a more fine template could improve prediction accuracy.
All Author(s) ListBénédicte Maréchal, Peipeng Liang, Lin Shi, Tianyi Qian, Defeng Wang, Tobias Kober, Alexis Roche, and Kuncheng Li
Name of ConferenceISMRM 25th Annual Meeting & Exhibition
Start Date of Conference22/04/2017
End Date of Conference27/04/2017
Place of ConferenceHonolulu, Hawaii
Country/Region of ConferenceUnited States of America
Year2017
LanguagesEnglish-United Kingdom

Last updated on 2018-20-01 at 18:04