Aganj Iman, Lenglet Christophe, Sapiro Guillermo
Department of Electrical and Computer Engineering, University of Minnesota, USA.
Med Image Comput Comput Assist Interv. 2010;13(Pt 2):84-91. doi: 10.1007/978-3-642-15745-5_11.
By revealing complex fiber structure through the orientation distribution function (ODF), q-ball imaging has recently become a popular reconstruction technique in diffusion-weighted MRI. In this paper, we propose an analytical dimension reduction approach to ODF maxima extraction. We show that by expressing the ODF, or any antipodally symmetric spherical function, in the common fourth order real and symmetric spherical harmonic basis, the maxima of the two-dimensional ODF lie on an analytically derived one-dimensional space, from which we can detect the ODF maxima. This method reduces the computational complexity of the maxima detection, without compromising the accuracy. We demonstrate the performance of our technique on both artificial and human brain data.
通过取向分布函数（ODF）揭示复杂的纤维结构，q球成像最近已成为扩散加权磁共振成像中一种流行的重建技术。在本文中，我们提出了一种用于提取ODF最大值的解析降维方法。我们表明，通过在常见的四阶实对称球谐基中表示ODF或任何反对称球函数，二维ODF的最大值位于一个解析推导的一维空间上，我们可以从中检测ODF最大值。该方法降低了最大值检测的计算复杂度，同时不影响准确性。我们在人工和人脑数据上展示了我们技术的性能。
