基于多层Mumford-Shah向量值图像分割、去噪与重建模型(HMSMv)和光滑样条曲线拟合技术,提出了一种用于计算机辅助青光眼诊断的视乳头图像视杯和视盘重建、分割与度量的新方法。首先,采用HMSMv分割和重建视杯和视盘;然后,基于重建的视乳头图像,结合青光眼视乳头图像杯、盘的先验知识,提取视杯和视盘特征矩形和边缘特征点;最后,采用光滑样条曲线拟合技术,重建被血管遮挡的视杯和视盘部分边缘,并计算杯盘比等病理特征参数值。不同青光眼病人的视乳头图像杯盘重建、分割与度量实验结果表明,该方法能克服噪声污染、血管遮挡、光照不均匀、对比度小、个体间差异大等视网膜图像分割中固有的困难,并有效重建、分割与度量青光眼彩色视乳头图像中的视杯和视盘。
A method was proposed to reconstruct, segment and measure the optic cup and disk in a color image of optic nerve heads for the computer aided diagnostics of glaucoma diseases. First, a hierarchical Mumford-Shah model was employed to reconstruct the optic cup and disk. Then, the optic cup and disk characteristic rectangles and edge points were extracted based on the color reconstruct image of an optic nerve head by incorporating the pr/or knowledge of the optic cup and disk shapes, Finally, smoothing spline curve fitting was resorted to reconstruct the edges of the optic cup and disk obscured by blood vessels, and the measurements of the optic cup and disk were estimated. Tests were conducted on the color optic nerve head images of different glaucoma patients. Results showed that the proposed method was able to handle the images which were with poor quality, very low contrast, obscure due to blood vessels, and distinct inter-differences of individuals, and thus to effectively segment, reconstruct and measure the optic cup and disk in a color image of optic nerve heads.