Rohlfing Torsten
Neuroscience Program, SRI International, Menlo Park, CA, USA
Med Image Comput Comput Assist Interv. 2006;9(Pt 1):207-14. doi: 10.1007/11866565_26.
This work investigates the effects of nonrigid transformation model and deformation constraints on the results of deformation-based morphometry (DBM) studies. We evaluate three popular registration algorithms: a B-spline algorithm with several different constraint terms, Thirion's demons algorithm, and a curvature PDE-based algorithm. All algorithms produced virtually identical overlaps of corresponding structures, but the underlying deformation fields were very different, and the Jacobian determinant values within homogeneous structures varied dramatically. In several cases, we observed bi-modal distributions of Jacobians within a region that violate the assumption of gaussianity that underlies many statistical tests. Our results demonstrate that, even with perfect overlap of corresponding structures, the statistics of Jacobian values are affected by bias due to design elements of the particular nonrigid registration. These findings are not limited to DBM, but also apply to voxel-based morphometry to the extent that it includes a Jacobian-based correction step ("modulation").
这项工作研究了非刚性变换模型和变形约束对基于变形的形态测量学（DBM）研究结果的影响。我们评估了三种常用的配准算法：一种带有几种不同约束项的B样条算法、蒂里翁的魔鬼算法以及一种基于曲率偏微分方程的算法。所有算法在对应结构的重叠方面几乎产生相同的结果，但潜在的变形场却大不相同，并且均匀结构内的雅可比行列式值变化很大。在几种情况下，我们在一个区域内观察到雅可比行列式的双峰分布，这违反了许多统计检验所基于的高斯性假设。我们的结果表明，即使对应结构完美重叠，雅可比行列式值的统计也会受到特定非刚性配准设计元素导致的偏差影响。这些发现不仅限于DBM，而且在基于体素的形态测量学中只要包含基于雅可比行列式的校正步骤（“调制”）也同样适用。
