Murgasova Maria, Dyet Leigh, Edwards David, Rutherford Mary, Hajnal Joseph V, Rueckert Daniel
Visual Information Processing Group, Department of Computing, Imperial College London.
Med Image Comput Comput Assist Interv. 2006;9(Pt 1):687-94. doi: 10.1007/11866565_84.
This paper describes an automatic tissue segmentation algorithm for brain MRI of young children. Existing segmentation methods developed for the adult brain do not take into account the specific tissue properties present in the brain MRI of young children. We examine the suitability of state-of-the-art methods developed for the adult brain when applied to the segmentation of the young child brain MRI. We develop a method of creation of a population-specific atlas from young children using a single manual segmentation. The method is based on non-linear propagation of the segmentation into population and subsequent affine alignment into a reference space and averaging. Using this approach we significantly improve the performance of the popular EM segmentation algorithm on brain MRI of young children.
本文描述了一种针对幼儿脑部磁共振成像(MRI)的自动组织分割算法。现有的针对成人大脑开发的分割方法没有考虑幼儿脑部MRI中存在的特定组织特性。我们研究了为成人大脑开发的先进方法应用于幼儿脑部MRI分割时的适用性。我们开发了一种方法,通过单次手动分割从幼儿创建特定人群图谱。该方法基于将分割结果非线性传播到人群中,随后进行仿射对齐到参考空间并求平均值。使用这种方法,我们显著提高了流行的期望最大化(EM)分割算法在幼儿脑部MRI上的性能。