Kazemi K, Grebe R, Moghaddam Abrishami H, Lagadec P, Gondry-Jouet C, Wallois F
Faculté de Médecine, Université de Picardie Jules Verne, Amiens, 80036, France.
Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:5509-12. doi: 10.1109/IEMBS.2007.4353593.
In this paper, we present the design and implementation of a 3D digital phantom of the neonatal brain. Commonly used digital brain phantoms (e.g. BrainWeb) are based on adults' brains. With the increasing interest in computer aided analysis of neonatal Magnetic Resonance (MR) images, it becomes necessary to create a special digital phantom for neonatal brains. This is because of the pronounced differences not only in size but more important in geometrical proportions of different brain tissues in adults and neonates and the additional need to subdivide the white matter of neonatal brains into two different types. Thus, the here created neonatal brain phantom consists of 6 different tissue types: scalp, skull, gray matter, myelinated and non-myelinated white matter and cerebrospinal fluid. Every voxel has a vector consisting of 6 probabilities of being part of one of these six tissues. The digital brain phantom will be used for simulation of tomographic images of the newborns' head and may serve as well as an evaluation data set for comparison of analysis methods for neonatal MR images, e.g. segmentation/registration algorithms, providing the possibility of controlled degradation of image data.
在本文中,我们展示了新生儿脑三维数字模型的设计与实现。常用的数字脑模型(如BrainWeb)是基于成人脑的。随着对新生儿磁共振(MR)图像计算机辅助分析的兴趣日益增加,有必要为新生儿脑创建一个特殊的数字模型。这是因为不仅在大小上,而且更重要的是在成人和新生儿不同脑组织的几何比例上存在显著差异,并且需要将新生儿脑的白质进一步细分为两种不同类型。因此,这里创建的新生儿脑模型由6种不同的组织类型组成:头皮、颅骨、灰质、有髓和无髓白质以及脑脊液。每个体素都有一个向量,该向量由属于这六种组织之一的6个概率组成。该数字脑模型将用于模拟新生儿头部的断层图像,也可作为评估数据集,用于比较新生儿MR图像分析方法,如分割/配准算法,为图像数据的可控降解提供可能性。