School of Ophthalmology and Optometry, Wenzhou Medical College, Zhejiang, China.
Eye Contact Lens. 2012 May;38(3):150-7. doi: 10.1097/ICL.0b013e3182499b64.
The aim of this study was to investigate the feasibility of automatic segmentation of the central corneal thickness (CCT) and epithelial thickness (ET) of the human cornea obtained with different spectral domain optical coherence tomography (OCT) instruments.
Ten left eyes from 10 healthy subjects with a mean age of 22.5 ± 1.5 years participated in this study. A custom-built ultra-high resolution OCT (UHR-OCT) with a 3-μm axial resolution, ultralong scan depth OCT (UL-OCT) with a 7.5-μm resolution, and commercial RTVue OCT with a 5-μm resolution were used to image the cornea. An automated segmentation algorithm was developed to process the OCT images and yield the CCT and ET. The measurement was verified by a manual measurement.
The automatic algorithm successfully processed the central thickness of the cornea and corneal epithelium for all images. The average CCT obtained by the automatic segmentation algorithm was 528.1 ± 22.4 μm, 526.1 ± 23.4 μm, and 525.2 ± 23.7 μm for UHR-OCT, UL-OCT, and RTVue, respectively. The average ET was 53.2 ± 2.0 μm, 54.1 ± 3.0 μm, and 52.1 ± 2.5 μm for UHR-OCT, UL-OCT, and RTVue, respectively. These measurements were in agreement with those of the manual method for the CCT (all r>0.997, P<0.05) and for the ET (all r>0.71, P<0.05).
The algorithm seemed to be feasible for automatically segmenting the CCT and ET in OCT images using these tested OCT devices. The segmented results were equivalent to that obtained with the manual method.
本研究旨在探讨使用不同谱域光学相干断层扫描(OCT)仪器自动分割人眼角膜中央角膜厚度(CCT)和上皮厚度(ET)的可行性。
本研究纳入 10 名平均年龄为 22.5±1.5 岁的健康左眼受试者。使用具有 3μm 轴向分辨率的定制超高分辨率 OCT(UHR-OCT)、具有 7.5μm 分辨率的超长扫描深度 OCT(UL-OCT)和商用 RTVue OCT 对角膜进行成像。开发了一种自动分割算法来处理 OCT 图像并获得 CCT 和 ET。通过手动测量对测量结果进行验证。
自动算法成功处理了所有图像的角膜中央厚度和角膜上皮。自动分割算法获得的平均 CCT 分别为 UHR-OCT、UL-OCT 和 RTVue 的 528.1±22.4μm、526.1±23.4μm 和 525.2±23.7μm。平均 ET 分别为 UHR-OCT、UL-OCT 和 RTVue 的 53.2±2.0μm、54.1±3.0μm 和 52.1±2.5μm。这些测量值与 CCT(均 r>0.997,P<0.05)和 ET(均 r>0.71,P<0.05)的手动方法测量值一致。
该算法似乎可用于使用这些经过测试的 OCT 设备自动分割 OCT 图像中的 CCT 和 ET。分割结果与手动方法获得的结果相当。