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鉴定的使用神经影像学数据的与疾病-相关的的空间协方差模式
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JoVE Journal Medicina
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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鉴定的使用神经影像学数据的与疾病-相关的的空间协方差模式

DOI:
10.3791/50319-v

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14:27 min

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June 26, 2013

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, , , , , ,
1Center for Neurosciences,The Feinstein Institute for Medical Research

Capítulos

  • 00:05Título
  • 03:06Data Collection and Preprocessing
  • 04:34Perform Multivariate SSM/PCA
  • 08:47Pattern Biomarker Derivation
  • 10:36Results: Identification of Disease-related Spatial Covariance Patterns
  • 13:08Conclusion

Summary

Tadução automática

Tadução automática

多元技术，包括主成分分析（PCA）已经脑功能图像用于识别签名区域变化模式。我们已经开发了一种算法来识别重复的网络神经退行性疾病的诊断，评估病情恶化，患者人群的治疗效果和客观评价的生物标志物。

Tags

Keywords: Spatial Covariance PatternsNeuroimaging DataScaled Subprofile Model (SSM)Group Invariant Subprofile (GIS)PCAFDG PETParkinson’s DiseaseDisease-related PatternsNetwork-specific ContributionsDifferential DiagnosisDisease ProgressionTreatment Effects

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