Computer Vision and Robotics Group, University of Girona, Campus Montilivi, Ed. P-IV, 17071, Girona, Spain,
Neuroinformatics. 2014 Jul;12(3):365-79. doi: 10.1007/s12021-013-9216-z.
Registration is a key step in many automatic brain Magnetic Resonance Imaging (MRI) applications. In this work we focus on longitudinal registration of brain MRI for Multiple Sclerosis (MS) patients. First of all, we analyze the effect that MS lesions have on registration by synthetically eliminating some of the lesions. Our results show how a widely used method for longitudinal registration such as rigid registration is practically unconcerned by the presence of MS lesions while several non-rigid registration methods produce outputs that are significantly different. We then focus on assessing which is the best registration method for longitudinal MRI images of MS patients. In order to analyze the results obtained for all studied criteria, we use both descriptive statistics and statistical inference: one way ANOVA, pairwise t-tests and permutation tests.
注册是许多自动脑磁共振成像（MRI）应用中的关键步骤。在这项工作中，我们专注于多发性硬化症（MS）患者的脑 MRI 纵向配准。首先，我们通过综合消除一些病变来分析 MS 病变对配准的影响。我们的结果表明，像刚性配准这样广泛使用的纵向配准方法实际上对 MS 病变的存在并不关心，而几种非刚性配准方法产生的输出则有明显的不同。然后，我们专注于评估哪种方法是 MS 患者纵向 MRI 图像的最佳配准方法。为了分析所有研究标准的结果，我们同时使用描述性统计和统计推断：单因素方差分析、成对 t 检验和置换检验。
