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SURFACE FLUID REGISTRATION OF CONFORMAL REPRESENTATION: APPLICATION TO DETECT DISEASE BURDEN AND GENETIC INFLUENCE ON HIPPOCAMPUS

机译:共形代表的表面流体配准:在疾病负担和遗传对海马的影响中的应用

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摘要

In this paper, we develop a new automated surface registration system based on surface conformal parameterization by holomorphic 1-forms, inverse consistentsurface fluid registration, and multivariate tensor-based morphometry (mTBM). First, we conformally map a surface onto a planar rectangle space with holomorphic 1-forms. Second, we compute surface conformal representation by combining its local conformal factor and mean curvature and linearly scale the dynamic range of the conformal representation to form the feature image of the surface. Third, we align the feature image with a chosen template image via the fluid image registration algorithm, which has been extended into the curvilinear coordinates to adjust for the distortion introduced by surface parameterization. The inverse consistent image registration algorithm is also incorporated in the system to jointly estimate the forward and inverse transformations between the study and template images. This alignment induces a corresponding deformation on the surface. We tested the system on Alzheimer's Disease Neuroimaging Initiative (ADNI) baseline dataset to study AD symptoms on hippocampus. In our system, by modeling a hippocampus as a 3D parametric surface, we nonlinearly registered each surface with a selected template surface. Then we used mTBM to analyze the morphometrydifference between diagnostic groups. Experimental results show that the new system has better performance than two publically available subcortical surface registration tools: FIRST and SPHARM. We also analyzed the genetic influence of the Apolipoprotein E ε4 allele (ApoE4),which is considered as the most prevalent risk factor for AD.Our work successfully detected statistically significant difference between ApoE4 carriers and non-carriers in both patients of mild cognitive impairment (MCI) and healthy control subjects. The results show evidence that the ApoE genotype may be associated with accelerated brain atrophy so that our workprovides a new MRI analysis tool that may help presymptomatic AD research.
机译:在本文中,我们开发了一种新的自动表面配准系统,该系统基于全形1形式的表面共形参数化,逆一致表面流体配准和基于多张量的形态学(mTBM)。首先,我们将一个表面保形地映射到具有全纯1形式的平面矩形空间。其次,我们通过结合其局部保形因子和平均曲率来计算表面保形表示,并线性缩放该保形表示的动态范围以形成表面的特征图像。第三,我们通过流体图像配准算法将特征图像与选定的模板图像对齐,该算法已扩展到曲线坐标中,以适应由表面参数化引入的变形。逆一致图像配准算法也被并入系统中,以共同估计研究图像和模板图像之间的正向和逆变换。这种对准在表面上引起相应的变形。我们在阿尔茨海默氏病神经影像学倡议(ADNI)基线数据集中测试了该系统,以研究海马体的AD症状。在我们的系统中,通过将海马建模为3D参数化曲面,我们将每个曲面与选定的模板曲面非线性配准。然后我们使用mTBM分析诊断组之间的形态学差异。实验结果表明,该新系统的性能优于两个公开的皮质下表面注册工具:FIRST和SPHARM。我们还分析了载脂蛋白Eε4等位基因(ApoE4)的遗传影响,该等位基因被认为是AD的最普遍危险因素。 MCI)和健康对照组。结果表明,有证据表明ApoE基因型可能与加速的脑萎缩有关,因此我们的工作提供了一种新的MRI分析工具,可以帮助症状前AD研究。

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