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Full-Text Articles in Medicine and Health Sciences
Characterization Of Disease-Related Covariance Topographies With Ssmpca Toolbox: Effects Of Spatial Normalization And Pet Scanners, S. C. Peng, Y. L. Ma, P. G. Spetsieris, P. Mattis, Andrew Feigin, V. Dhawan, D. Eidelberg
Characterization Of Disease-Related Covariance Topographies With Ssmpca Toolbox: Effects Of Spatial Normalization And Pet Scanners, S. C. Peng, Y. L. Ma, P. G. Spetsieris, P. Mattis, Andrew Feigin, V. Dhawan, D. Eidelberg
Journal Articles
To generate imaging biomarkers from disease-specific brain networks, we have implemented a general toolbox to rapidly perform scaled subprofile modeling (SSM) based on principal component analysis (PCA) on brain images of patients and normals. This SSMPCA toolbox can define spatial covariance patterns whose expression in individual subjects can discriminate patients from controls or predict behavioral measures. The technique may depend on differences in spatial normalization algorithms and brain imaging systems. We have evaluated the reproducibility of characteristic metabolic patterns generated by SSMPCA in patients with Parkinson's disease (PD). We used [F-18]fluorodeoxyglucose PET scans from patients with PD and normal controls. …