Statistical 3D shape analysis of gender differences in lateral ventricles

Qing He; Dmitriy Karpman; Ye Duan

doi:10.1117/12.839984

9 March 2010 Statistical 3D shape analysis of gender differences in lateral ventricles

Qing He, Dmitriy Karpman, Ye Duan

Proceedings Volume 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging; 762609 (2010) https://doi.org/10.1117/12.839984
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

This paper aims at analyzing gender differences in the 3D shapes of lateral ventricles, which will provide reference for the analysis of brain abnormalities related to neurological disorders. Previous studies mostly focused on volume analysis, and the main challenge in shape analysis is the required step of establishing shape correspondence among individual shapes. We developed a simple and efficient method based on anatomical landmarks. 14 females and 10 males with matching ages participated in this study. 3D ventricle models were segmented from MR images by a semiautomatic method. Six anatomically meaningful landmarks were identified by detecting the maximum curvature point in a small neighborhood of a manually clicked point on the 3D model. Thin-plate spline was used to transform a randomly selected template shape to each of the rest shape instances, and the point correspondence was established according to Euclidean distance and surface normal. All shapes were spatially aligned by Generalized Procrustes Analysis. Hotelling T² twosample metric was used to compare the ventricle shapes between males and females, and False Discovery Rate estimation was used to correct for the multiple comparison. The results revealed significant differences in the anterior horn of the right ventricle.

Citation Download Citation

Qing He, Dmitriy Karpman, and Ye Duan "Statistical 3D shape analysis of gender differences in lateral ventricles", Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 762609 (9 March 2010); https://doi.org/10.1117/12.839984

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