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Abstract #2897

Improving the Reliability of Between Group Analyses in DTI-FA Analyses by Detecting and Removing Anatomical Anomalies

Ramtilak Gattu1, Zhifeng Kou2, Robert Welch3, Valerie Mika4, Hardik Doshi4, Ewart Mark Haacke2, Randall Benson5

1Radiology, Wayne State University, Detroit, MI, United States; 2Biomedical Engineering, Radiology, Wayne State University, Detroit, MI, United States; 3Emergency Medicine, Wayne State University School of Medicine, Detroit, MI, United States; 4Biomedical Engineering, Wayne State University, Detroit, MI, United States; 5Center for Neurological Studies, Novi, MI, United States

A method of removing anomalous anatomy is described to be applied to diffusion tensor image processing involving between subject comparison. The method first attempts to spatially register all images into a common space but in some cases the registration is strained by anatomical anomalies which would result in artifactual results if not accounted for. The method described utilizes sampled voxelwise FA variance from controls in order to exclude or mask outlier values over spatial scales consistent with anatomical anomalies. The results reported indicated the value of the method in reducing false positive artifacts in DTI analysis.