基于混合水平集模型的CT颅面眼眶分割

A Hybrid Level Set Model with Application to the Segmentation of Eye Socket

提出一种混和水平集模型,用于颅面整复的眼眶分割。与一般水平集模型相比,混和水平集模型同时结合了区域和边缘信息,从而使得其具有较高的鲁棒性和准确性,解决了单纯基于边缘的水平集模型容易产生边缘泄露的问题。采用混合水平集模型分割的结果可用于三维重建和三维充填物计算,从而达到计算机辅助指导临床手术的目的。实验证明混和水平集模型在眼眶分割中取得了很好的效果。

In this paper, we propose a hybrid level set model with application to the segmentation of eye socket. Compared with other level set methods, the hybrid model is more robust and accurate due to the combination of region and boundary information. It solves the leaking problem of boundary based level set method. The segment results of hybrid level set model can be used in 3-D eye socket reconstruction and calculation of hydroxyapatlte implant, which are useful in computer-aided surgery. Experiments have shown that hybrid level set model has very good performance in the segmentation of eye socket.