Chen Qiang, de Sisternes Luis, Leng Theodore, Zheng Luoluo, Kutzscher Lauren, Rubin Daniel L
School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China ; Department of Radiology and Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA 94305, USA.
Department of Radiology and Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA 94305, USA.
Biomed Opt Express. 2013 Nov 1;4(12):2729-50. doi: 10.1364/BOE.4.002729. eCollection 2013.
Geographic atrophy (GA) is a condition that is associated with retinal thinning and loss of the retinal pigment epithelium (RPE) layer. It appears in advanced stages of non-exudative age-related macular degeneration (AMD) and can lead to vision loss. We present a semi-automated GA segmentation algorithm for spectral-domain optical coherence tomography (SD-OCT) images. The method first identifies and segments a surface between the RPE and the choroid to generate retinal projection images in which the projection region is restricted to a sub-volume of the retina where the presence of GA can be identified. Subsequently, a geometric active contour model is employed to automatically detect and segment the extent of GA in the projection images. Two image data sets, consisting on 55 SD-OCT scans from twelve eyes in eight patients with GA and 56 SD-OCT scans from 56 eyes in 56 patients with GA, respectively, were utilized to qualitatively and quantitatively evaluate the proposed GA segmentation method. Experimental results suggest that the proposed algorithm can achieve high segmentation accuracy. The mean GA overlap ratios between our proposed method and outlines drawn in the SD-OCT scans, our method and outlines drawn in the fundus auto-fluorescence (FAF) images, and the commercial software (Carl Zeiss Meditec proprietary software, Cirrus version 6.0) and outlines drawn in FAF images were 72.60%, 65.88% and 59.83%, respectively.
地图样萎缩（GA）是一种与视网膜变薄和视网膜色素上皮（RPE）层缺失相关的病症。它出现在非渗出性年龄相关性黄斑变性（AMD）的晚期，可导致视力丧失。我们提出了一种用于光谱域光学相干断层扫描（SD-OCT）图像的半自动GA分割算法。该方法首先识别并分割RPE和脉络膜之间的表面，以生成视网膜投影图像，其中投影区域限于视网膜的一个子体积，在该子体积中可以识别GA的存在。随后，采用几何活动轮廓模型自动检测并分割投影图像中GA的范围。分别使用两个图像数据集，一个由来自8名GA患者的12只眼睛的55次SD-OCT扫描组成，另一个由56名GA患者的56只眼睛的56次SD-OCT扫描组成，对所提出的GA分割方法进行定性和定量评估。实验结果表明，所提出的算法可以实现高分割精度。我们提出的方法与SD-OCT扫描中绘制的轮廓之间、我们的方法与眼底自发荧光（FAF）图像中绘制的轮廓之间以及商业软件（卡尔蔡司医疗技术公司专有软件，Cirrus版本6.0）与FAF图像中绘制的轮廓之间的平均GA重叠率分别为72.60%、65.88%和59.83%。
