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12 May 2004 Correction scheme for multiple correlated statistical tests in local shape analysis
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In neuroimaging research, shape analysis has become a field of great interest due to the ability to locate morphological brain changes between different groups. Currently, many local shape analysis approaches fail to correct for their high number of correlated statistical tests. This can result in an overly optimistic estimate of the local shape analysis. This paper presents a correction scheme for objects described by the parametrized 3D closed surface description SPHARM. The SPHARM parameterization was determined via an area preserving, distortion minimizing optimization. The correction scheme decomposes the object surface into overlapping planar images via a cylindrical equal area projection of the parameterization. The images are individually analyzed with the SnPM/SPM package using a voxel-level non-parametric multiple testing procedure based on permutation tests. The correction scheme employs conservative tests resulting in a pessimistic estimate. We present an application of the correction scheme to the shape similarity analysis of lateral ventricles
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Martin A. Styner and Guido Gerig "Correction scheme for multiple correlated statistical tests in local shape analysis", Proc. SPIE 5370, Medical Imaging 2004: Image Processing, (12 May 2004);


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