Silveira Margarida, Aguiar Pedro M Q
Institute for Systems and Robotics/IST, Portugal.
Annu Int Conf IEEE Eng Med Biol Soc. 2008;2008:5378-81. doi: 10.1109/IEMBS.2008.4650430.
The analysis of 3D SPECT brain images requires several pre-processing steps such as registration, intensity normalization and brain extraction. Usually, registration is performed before intensity normalization, which requires robust registration methods, such as those based on the maximization of the Mutual Information (MI), which are computationally complex. In this paper we propose using a computationally simple method to perform the simultaneous registration and intensity normalization of SPECT brain perfusion images. The approach, which extends to 3D data a method originally proposed in [1] for 2D photographic images, estimates in alternate steps the intensity normalization parameters and the registration parameters. Our experiments, with real SPECT images, show that the proposed registration method leads to results similar to those obtained by using more expensive algorithms such as those based on the MI criterion.
对三维单光子发射计算机断层扫描(SPECT)脑图像的分析需要几个预处理步骤,如配准、强度归一化和脑提取。通常,配准在强度归一化之前进行,这需要强大的配准方法,比如基于互信息(MI)最大化的方法,这些方法计算复杂。在本文中,我们提出使用一种计算简单的方法来同时进行SPECT脑灌注图像的配准和强度归一化。该方法将最初在[1]中针对二维摄影图像提出的一种方法扩展到三维数据,在交替步骤中估计强度归一化参数和配准参数。我们使用真实SPECT图像进行的实验表明,所提出的配准方法产生的结果与使用更昂贵的算法(如基于MI准则的算法)所获得的结果相似。