Visual Optics Group, Department of Optics and Photonics, Wrocław University of Science and Technology, Wrocław, Poland.
Contact Lens and Visual Optics Laboratory, School of Optometry and Vision Science, Queensland University of Technology, Brisbane, Australia.
Optom Vis Sci. 2021 Feb 1;98(2):127-136. doi: 10.1097/OPX.0000000000001637.
This study evaluates the reliability and validity of an automatic method of the external and internal limbal points identification from anterior segment optical coherence tomography (OCT) images in comparison with manual delineation.
The purpose of this work was to evaluate the repeatability and precision of a previously proposed automatic method of external and internal limbal points identification and to compare them with the manual delineation by experienced clinicians in terms of limbus diameter.
Optical coherence tomography tomograms obtained for 12 healthy volunteers without a history of eye diseases were analyzed. Fifteen OCT tomograms were captured for each patient. For all the images, the external and internal limbal points were determined using both the automatic and manual methods. The external and internal limbus diameters were used as the comparative parameter between the methods under consideration. The statistical analysis included mean, standard deviation, the Passing-Bablok regression, and the Pearson correlation coefficient.
A strong linear dependence between the automatic and manual methods was identified. While compared with the subjective estimates from clinicians, the automatic technique overestimated the external limbus diameter (bias equals 0.21 mm for optometrist and 0.23 mm for ophthalmologist) and slightly underestimated the internal limbus diameter (bias equals 0.13 mm for optometrist and 0.04 mm for ophthalmologist). The automatic method showed significantly better repeatability than the manual method in the case of external limbal points identification and comparably high repeatability for internal limbal points recognition.
Because of high precision and excellent repeatability, the automatic method of limbal points identification may be successfully used for estimation of the dynamic changes in the geometry of the anterior segment of the eye, where the large number of captured OCT images needs to be processed automatically with high precision.
本研究评估了一种自动方法从眼前节光学相干断层扫描（OCT）图像中识别外部和内部角膜缘点的可靠性和有效性，并与手动描绘进行比较。
本工作的目的是评估先前提出的自动方法识别外部和内部角膜缘点的重复性和精度，并在角膜缘直径方面将其与经验丰富的临床医生的手动描绘进行比较。
分析了 12 名无眼部疾病史的健康志愿者的 OCT 断层扫描图像。每位患者采集了 15 张 OCT 断层扫描图像。对于所有图像，使用自动和手动方法确定外部和内部角膜缘点。将外部和内部角膜缘直径用作考虑方法之间的比较参数。统计分析包括平均值、标准差、Passing-Bablok 回归和 Pearson 相关系数。
确定了自动和手动方法之间存在很强的线性相关性。与临床医生的主观估计相比，自动技术高估了外部角膜缘直径（视光师的偏差为 0.21 毫米，眼科医生的偏差为 0.23 毫米），并且略微低估了内部角膜缘直径（视光师的偏差为 0.13 毫米，眼科医生的偏差为 0.04 毫米）。在外部角膜缘点识别方面，自动方法的重复性明显优于手动方法，而在内部角膜缘点识别方面的重复性也很高。
由于具有高精度和出色的可重复性，因此可以成功地将自动角膜缘点识别方法用于估计眼前节几何形状的动态变化，在这种情况下，需要大量捕获的 OCT 图像以高精度自动进行处理。
