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Segmentation of the Geographic Atrophy in Spectral-Domain Optical Coherence Tomography and Fundus Autofluorescence Images

机译:光谱域光学相干断层扫描和眼底自发荧光图像中的地理萎缩的分割

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Purpose.: Geographic atrophy (GA) is the atrophic late-stage manifestation of age-related macular degeneration (AMD), which may result in severe vision loss and blindness. The purpose of this study was to develop a reliable, effective approach for GA segmentation in both spectral-domain optical coherence tomography (SD-OCT) and fundus autofluorescence (FAF) images using a level seta??based approach and to compare the segmentation performance in the two modalities. Methods.: To identify GA regions in SD-OCT images, three retinal surfaces were first segmented in volumetric SD-OCT images using a double-surface graph search scheme. A two-dimensional (2-D) partial OCT projection image was created from the segmented choroid layer. A level set approach was applied to segment the GA in the partial OCT projection image. In addition, the algorithm was applied to FAF images for the GA segmentation. Twenty randomly chosen macular SD-OCT (Zeiss Cirrus) volumes and 20 corresponding FAF (Heidelberg Spectralis) images were obtained from 20 subjects with GA. The algorithm-defined GA region was compared with consensus manual delineation performed by certified graders. Results.: The mean Dice similarity coefficients (DSC) between the algorithm- and manually defined GA regions were 0.87 ?± 0.09 in partial OCT projection images and 0.89 ?± 0.07 in registered FAF images. The area correlations between them were 0.93 (P 0.001) in partial OCT projection images and 0.99 (P 0.001) in FAF images. The mean DSC between the algorithm-defined GA regions in the partial OCT projection and registered FAF images was 0.79 ?± 0.12, and the area correlation was 0.96 (P 0.001). Conclusions.: A level set approach was developed to segment GA regions in both SD-OCT and FAF images. This approach demonstrated good agreement between the algorithm- and manually defined GA regions within each single modality. The GA segmentation in FAF images performed better than in partial OCT projection images. Across the two modalities, the GA segmentation presented reasonable agreement.
机译:目的:地理萎缩(GA)是年龄相关性黄斑变性(AMD)的萎缩性晚期表现,可能导致严重的视力丧失和失明。这项研究的目的是开发一种可靠,有效的方法,使用基于水平seta ??方法的光谱域光学相干断层扫描(SD-OCT)和眼底自发荧光(FAF)图像中的GA分割,并比较分割性能在两种方式中。方法:为了识别SD-OCT图像中的GA区域,首先使用双面图搜索方案在体积SD-OCT图像中分割了三个视网膜表面。从分割的脉络膜层创建二维(2-D)部分OCT投影图像。应用水平集方法对部分OCT投影图像中的GA进行分割。此外,该算法已应用于FAF图像中的GA分割。从20名患有GA的受试者中获得20个随机选择的黄斑SD-OCT(蔡司卷云)体积和20张相应的FAF(海德堡光谱)图像。将算法定义的GA区域与经过认证的评分员进行的共识手动划定进行了比较。结果:算法和手动定义的GA区域之间的平均Dice相似系数(DSC)在部分OCT投影图像中为0.87±0.09,在已注册的FAF图像中为0.89±0.07。它们之间的面积相关性在部分OCT投影图像中为0.93(P <0.001),在FAF图像中为0.99(P <0.001)。 OCT局部投影中的算法定义的GA区域与已注册的FAF图像之间的平均DSC为0.79±0.12,面积相关性为0.96(P <0.001)。结论:开发了一种水平集方法来分割SD-OCT和FAF图像中的GA区域。该方法证明了在每个单一模态内的算法区域和手动定义的GA区域之间的良好一致性。 FAF图像中的GA分割效果优于部分OCT投影图像。在这两种方式中,GA细分显示出合理的一致性。

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