Weighted Fourier series representation and its application to quantifying the amount of gray matter
Weighted Fourier series representation and its application to quantifying the amount of gray matter
复制标题
DOI：
10.1109/tmi.2007.892519
复制
发表时间：
2007-04-01
影响因子：
10.6
通讯作者：
Davidson, Richard J.
中科院分区：
文献类型：
--
作者：
Chung, Moo K.;Dalton, Kim M.;Davidson, Richard J.
我们提出了一种新的加权傅里叶级数（WFS）表示皮质表面。WFS表示是一种数据平滑技术，其提供作为基函数的线性组合的未知皮层边界的显式平滑函数估计。该表示的基本性质进行了研究与自伴偏微分方程和传统的球谐（SPHARM）表示。为了减少陡峭的计算需求，一个新的迭代残差拟合（IRF）算法的发展。它的计算和数值实现的问题进行了详细讨论。计算机代码也可在http://www.stat.wise.edu/-mchung/softwares/weighted-SPHARM/weighted-SIPHARM.html上查阅。作为一个例子，WFS被应用于定量的灰质的量在一组高功能自闭症患者。在WFS框架内，计算并比较皮质厚度和灰质密度。
We present a novel weighted Fourier series (WFS) representation for cortical surfaces. The WFS representation is a data smoothing technique that provides the explicit smooth functional estimation of unknown cortical boundary as a linear combination of basis functions. The basic properties of the representation are investigated in connection with a self-adjoint partial differential equation and the traditional spherical harmonic (SPHARM) representation. To reduce steep computational requirements, a new iterative residual fitting (IRF) algorithm is developed. Its computational and numerical implementation issues are discussed in detail. The computer codes are also available at http://www.stat.wise.edu/-mchung/softwares/weighted-SPHARM/weighted-SIPHARM.html. As an illustration, the WFS is applied in quantifying the amount of gray matter in a group of high functioning autistic subjects. Within the WFS framework, cortical thickness and gray matter density are computed and compared.