A new quality assessment parameter for optical coherence tomography
A new quality assessment parameter for optical coherence tomography
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DOI：
10.1136/bjo.2004.059824
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发表时间：
2006-02-01
影响因子：
4.1
通讯作者：
Schuman, JS
中科院分区：
文献类型：
--
作者：
Stein, DM;Ishikawa, H;Schuman, JS
目的：创建一种新的、自动化的光学相干断层扫描（OCT）图像质量评估方法，并将其图像质量判别能力与质量评估参数信噪比（SNR）和信号强度（SS）进行比较。方法：创建了一种新的OCT图像质量评估参数——质量指数（QI）。使用最新的 StratusOCT 系统分析 OCT 图像（线性黄斑扫描、视盘周围圆形扫描和视神经乳头扫描）。收集每幅图像的 SNR 和 SS。 QI 是使用我们自己设计的软件程序根据图像直方图信息计算的。为了评估这些参数的性能，将结果与三名 OCT 专家进行的主观三级评分（优秀、可接受和差）进行比较。结果：21 名受试者的 63 幅图像（正常、早期/中度和晚期青光眼各 7 幅）纳入本研究。受试者是从我们的 OCT 成像数据库中以连续和回顾性的方式选择的。优秀图像和较差图像之间（分别为 p = 0.04、p = 0.002 和 p < 0.001，Wilcoxon 检验）以及可接受图像和较差图像之间（分别为 p = 0.02、p < 0.001 和 p < 0.001），SNR、SS 和 QI 存在显着差异。只有 QI 显示优秀图像和可接受图像之间存在显着差异 (p = 0.001)。用于区分较差图像和优秀/可接受图像的接收者操作特征 (ROC) 曲线下面积分别为 0.68 (SNR)、0.89 (IQP) 和 0.99 (QI)。结论：QI 等质量指数可以允许对 OCT 图像质量进行自动客观和定量评估，其表现与人类专家观察者类似。
Aim: To create a new, automated method of evaluating the quality of optical coherence tomography (OCT) images and to compare its image quality discriminating ability with the quality assessment parameters signal to noise ratio (SNR) and signal strength (SS).Methods: A new OCT image quality assessment parameter, quality index (QI), was created. OCT images (linear macular scan, peripapillary circular scan, and optic nerve head scan) were analysed using the latest StratusOCT system. SNR and SS were collected for each image. QI was calculated based on image histogram information using a software program of our own design. To evaluate the performance of these parameters, the results were compared with subjective three level grading (excellent, acceptable, and poor) performed by three OCT experts.Results: 63 images of 21 subjects (seven each for normal, early/moderate, and advanced glaucoma) were enrolled in this study. Subjects were selected in a consecutive and retrospective fashion from our OCT imaging database. There were significant differences in SNR, SS, and QI between excellent and poor images (p = 0.04, p = 0.002, and p < 0.001, respectively, Wilcoxon test) and between acceptable and poor images ( p = 0.02, p < 0.001, and p < 0.001, respectively). Only QI showed significant difference between excellent and acceptable images (p = 0.001). Areas under the receiver operating characteristics (ROC) curve for discrimination of poor from excellent/acceptable images were 0.68 (SNR), 0.89 (IQP), and 0.99 (QI).Conclusion: A quality index such as QI may permit automated objective and quantitative assessment of OCT image quality that performs similarly to an expert human observer.