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首页> 外文会议>IEEE International Symposium on Computer-Based Medical Systems >Radiomics Textural Features Extracted from Subcortical Structures of Grey Matter Probability for Alzheimers Disease Detection.
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Radiomics Textural Features Extracted from Subcortical Structures of Grey Matter Probability for Alzheimers Disease Detection.

机译：从灰色物质概率的皮层下结构提取的放射性组学特征用于阿尔茨海默氏病的检测。

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Alzheimer's disease (AD) is characterized by a progressive deterioration of cognitive and behavioral functions as a result of the atrophy of specific regions of the brain. It is estimated that by 2050 there will be 131.5 million people affected. Thus, there is an urgent need to find biological markers for its early detection and monitoring. In this work, it is present an analysis of textural radiomics features extracted from a gray matter probability volume, in a set of individual subcortical regions, from a number of different atlases, to identify subject with AD in a MRI. Also, significant subcortical regions for AD detection have been identified using a ReliefF relevance test. Experimental results using the ADNI1 database have proven the potential of some of the tested radiomic features as possible biomarkers for AD/CN differentiation.
机译：阿尔茨海默氏病（AD）的特征是由于大脑特定区域萎缩导致认知和行为功能的逐步恶化。估计到2050年将有1.315亿人受到影响。因此，迫切需要寻找生物标记物以对其进行早期检测和监测。在这项工作中，目前对从多个不同的图册中的一组单个皮层下区域的灰质概率体积中提取的纹理放射学特征进行分析，以在MRI中识别患有AD的对象。此外，已经使用ReliefF相关性测试确定了用于AD检测的重要皮层下区域。使用ADNI1数据库进行的实验结果证明了某些经过测试的放射学特征作为AD / CN分化可能的生物标记物的潜力。

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