Early classification of Alzheimer’s Disease based on hippocampal texture features
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    Abstract:

    Alzheimer's Disease(AD) is a neurodegenerative disease. With the development of brain imaging, the accuracy of AD diagnosis has been well improved. However, there still lack of good markers to early diagnosis of AD. In order to find more stable biomarkers of AD, the hippocampus intensity, shape, grayscale gradient distribution and other characteristics are investigated by an Analysis Of Variance and post-hoc analysis so as to identify the alteration in AD and Mild Cognitive Impairment(MCI) in comparison to Normal Controls(NC). The results show that the Mini-Mental State Examination(MMSE) scores are significantly associated with the radiomic features of the bilateral hippocampus. The classification analysis with the Support Vector Machine(SVM) shows that an accuracy of 86% can be obtained with leaving one out cross validation, which indicates that the hippocampal texture might be taken as one of the potential markers for AD.

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赵 坤,丁艳辉,张增强,周 波,姚洪祥,王 盼,冯 枫,郑元杰,刘 勇,张 熙.基于海马纹理特征的阿尔茨海默病早期识别[J]. Journal of Terahertz Science and Electronic Information Technology ,2019,17(1):136~140

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History
  • Received:June 27,2018
  • Revised:October 17,2018
  • Adopted:
  • Online: March 27,2019
  • Published: