Ji Chunhong, Yu Jinhua, Li Tianjie, Tian Lei, Huang Yifei, Wang Yuanyuan, Zheng Yongping
Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai, Shanghai, China.
Biomed Eng Online. 2015 Jun 4;14:53. doi: 10.1186/s12938-015-0036-2.
The measurement of dynamic parameters, such as the length of applanation and the amplitude of deformation, is significant for evaluating corneal properties. Most of the corneal properties (related to shape) including the anterior corneal curvature and the thickness of cornea can be easily measured using some existing techniques. However, they only provide the static or pseudo-dynamic analysis. Based on Corvis ST images, the dynamic features after corneal boundaries detection and parameter estimation will be helpful for corneal analysis.
The study included 40 eyes in normal group (ranging from 19 to 45 years old) and 30 eyes in keratoconus group (ranging from 16 to 40 years old). These eyes were examined by Corvis ST and for each one a sequence of 140 images was obtained. Besides, 11 subjects of each group were also tested by Pentacam.
By analyzing the video from the Corvis ST imaging, the fully dynamic curvature topography is proposed to evaluate the response of the anterior corneal surface to the air puff. The new method not only quantitatively measures the intact variation of anterior corneal surface but also provides an intuitive way to observe the dynamic change of the anterior corneal surface in the whole air stream process. The proposed method consists of three main steps: cornea segmentation, curvature estimation and integrated visualization. An automatic segmentation method based on the combination of prior knowledge with phase symmetry and asymmetry theory is firstly presented to detect the corneal boundaries. The Landau-new method is then used to estimate the anterior corneal surface. The corneal dynamic topography is finally obtained by combining the dynamic parameters with the original Corvis ST video, which is an improvement of the fusion technique proposed by Li et al.
By comparing the segmentation results with manual method and built-in method of Corvis ST, the accuracy and robustness of our proposed segmentation method is demonstrated. The correctness of the estimated corneal anterior curvatures is also evaluated by comparing it with that of Pentacam which is considered to be able to provide the first-class measurement currently. The dynamic topography may be used to distinguish the dynamic behavior of normal corneas from that of keratoconus.
测量动态参数,如压平长度和变形幅度,对于评估角膜特性具有重要意义。大多数角膜特性(与形状有关),包括角膜前曲率和角膜厚度,可使用一些现有技术轻松测量。然而,这些技术仅提供静态或准动态分析。基于Corvis ST图像,角膜边界检测和参数估计后的动态特征将有助于角膜分析。
该研究纳入了40只正常组眼睛(年龄在19至45岁之间)和30只圆锥角膜组眼睛(年龄在16至40岁之间)。这些眼睛通过Corvis ST进行检查,每只眼睛获取了140帧图像序列。此外,每组的11名受试者还接受了Pentacam检查。
通过分析Corvis ST成像的视频,提出了全动态曲率地形图以评估角膜前表面对气流冲击的反应。新方法不仅定量测量了角膜前表面的完整变化,还提供了一种直观的方式来观察整个气流过程中角膜前表面的动态变化。所提出的方法包括三个主要步骤:角膜分割、曲率估计和综合可视化。首先提出了一种基于先验知识与相位对称和不对称理论相结合的自动分割方法来检测角膜边界。然后使用Landau新方法估计角膜前表面。最后通过将动态参数与原始Corvis ST视频相结合获得角膜动态地形图,这是对Li等人提出的融合技术的改进。
通过将分割结果与手动方法和Corvis ST的内置方法进行比较,证明了我们提出的分割方法的准确性和鲁棒性。通过将估计的角膜前曲率与目前被认为能够提供一流测量的Pentacam的结果进行比较,也评估了其正确性。动态地形图可用于区分正常角膜和圆锥角膜的动态行为。