Rifa H, Bloch I, Hutchinson S, Wiart J, Garnero L
Ecole Nationaile Supérieure des Télécommunications, Département TSI, CNRS URA 820, Paris, France.
Med Image Anal. 2000 Sep;4(3):219-33. doi: 10.1016/s1361-8415(00)00016-5.
Segmentation of the skull in medical imagery is an important stage in applications that require the construction of realistic models of the head. Such models are used, for example, to simulate the behavior of electro-magnetic fields in the head and to model the electrical activity of the cortex in EEG and MEG data. In this paper, we present a new approach for segmenting regions of bone in MRI volumes using deformable models. Our method takes into account the partial volume effects that occur with MRI data, thus permitting a precise segmentation of these bone regions. At each iteration of the propagation of the model, partial volume is estimated in a narrow band around the deformable model. Our segmentation method begins with a pre-segmentation stage, in which a preliminary segmentation of the skull is constructed using a region-growing method. The surface that bounds the pre-segmented skull region offers an automatic 3D initialization of the deformable model. This surface is then propagated (in 3D) in the direction of its normal. This propagation is achieved using level set method, thus permitting changes to occur in the topology of the surface as it evolves, an essential capability for our problem. The speed at which the surface evolves is a function of the estimated partial volume. This provides a sub-voxel accuracy in the resulting segmentation.
在医学图像中对头骨进行分割是构建逼真头部模型的应用中的一个重要阶段。例如，这样的模型用于模拟头部中的电磁场行为以及对脑电图（EEG）和脑磁图（MEG）数据中的皮质电活动进行建模。在本文中，我们提出了一种使用可变形模型分割磁共振成像（MRI）体积中骨区域的新方法。我们的方法考虑了MRI数据中出现的部分容积效应，从而能够对这些骨区域进行精确分割。在模型传播的每次迭代中，在可变形模型周围的窄带中估计部分容积。我们的分割方法从预分割阶段开始，在该阶段使用区域生长方法构建头骨的初步分割。界定预分割头骨区域的表面为可变形模型提供了自动的三维初始化。然后该表面沿其法线方向（在三维中）传播。这种传播使用水平集方法实现，从而在表面演化时允许其拓扑结构发生变化，这是我们解决该问题的一项基本能力。表面演化的速度是估计的部分容积的函数。这在最终的分割中提供了亚体素精度。
