目的 视盘及视杯的检测对于分析眼底图像和视网膜视神经疾病计算机辅助诊断来说十分重要,利用医学眼底图像中视盘和视杯呈现椭圆形状这一特征,提出了椭圆约束下的多相主动轮廓模型,实现视盘视杯的同时精确分割。方法 该算法根据视盘视杯在灰度图像中具有不同的区域亮度,建立多相主动轮廓模型,然后将椭圆形约束内嵌于该模型中。通过对该模型的能量泛函进行求解,得到椭圆参数的演化方程。分割时首先设定两条椭圆形初始曲线,根据演化方程,驱动曲线分别向视盘和视杯方向进行移动。当轮廓线到达视盘、视杯边缘时,曲线停止演化。结果 在不同医学眼底图像中对算法进行验证,对算法抗噪性、不同初始曲线选取等进行了实验,并与多种算法进行了对比。实验结果表明,本文模型能够同时分割出视盘及视杯,与其他模型的分割结果相比,本文算法的分割结果更加准确。结论 本文算法可以精确分割医学眼底图像中的视盘和视杯,该算法不需要预处理,具有较强的鲁棒性和抗噪性。

Objective The detection of optic disc and cup is important in fundus image analysis and in the computer-aided diagnosis of optic nerve disease. In this study, an elliptical multiphase active contour model is proposed based on the oval shape of the optic disc and cup. The proposed algorithm can segment the optic disc and cup simultaneously and exactly. Method First, a multiphase active contour model is developed based on gray images of the optic disc and cup with different brightness levels. Afterward, the oval constraints are embedded in the model. The parametric equation of an ellipse can be obtained by finding the solution for the energy function of the model. Two oval initial curves are initially set. The evolution equation drive curves move toward the direction of the optic disc and cup. The curve evolution stops upon reaching the object contour border. Result The proposed algorithm is validated through experiments on its anti-noise ability and on the selection of different initial curves using different medical fundus images. The obtained results are compared with those of other algorithms. The experimental results show that unlike other models, the proposed model can simultaneously segment the optic disc and cup. The approach proposed in this paper can achieve superior image segmentation results. Conclusion A novel image segmentation method is presented in this work. The experimental results show that the method can accurately segment the optic disc and cup. The algorithm is proven to be not pretreatment, robust, and efficient.