## 4 Discussion  
This study assessed the performance of the segmentation algorithm of the OCT-HS100 to measure the thickness of eight individual retinal layers. The thickness was measured by automated layer segmentation software in nine ETDRS sectors. We show that there are variations in the repeatability both among the different sectors and the different layers. However, the repeatability was good in general for all eight retinal layers evaluated. The average thickness values of the individual retinal layers and its variability among the subjects reported in the present study are on a similar range to that of previously reported values [28,29]. The repeatability of thickness measurements of RNFL and GCL-IPL complexes have been reported extensively in many of the previous studies [6,20,21,22,23,28]. In the present study, we have evaluated the GCL and IPL layers separately and also evaluated the other individual layers in different ETDRS sectors. In general, there was some difference in the repeatability between the outer and inner sectors. One possible reason for this difference could be that the area of the inner sectors is much smaller than the outer sectors. When the segmentation software calculates the average thickness within the sector, any segmentation error will have a bigger impact on inner sectors than outer sectors. The present study used horizontal B-scans, and this could also have an impact on the repeatability of the different sectors [22]. The presence of blood vessels in the superior and inferior sectors can result in segmentation artefacts, and this could affect the mean thickness value of these sectors. The effect can also be more for inner sectors than outer sectors due to smaller area. In central sector, the repeatability varied between the different retinal layers. The best Sw was seen for OS and RPE and the worst for ONL. All of the inner retinal layers and OPL had a larger CoV in the central sector. The variability in the central sector is expected due to the thinner layers in that central sector. The variability for OPL could be due to the angle of the OCT's light beam. [PERSON] et al. [28] also reported that OPL had the worst repeatability. The CoV is inversely related to the actual thickness and hence, even if the Sw was smaller, the CoV can be larger. Larger variations in the repeatability among the sectors are seen in RNFL, OPL, and ONL. For RNFL, this variation can be due to the difference in the thickness among the sectors and that it is also the thinnest layer. For OPL and ONL, the variation could be mainly due to the difficulty in segmentation. The OPL contains both the photoreceptor synopses and Henle fiber layer. Depending upon the angle of the incident light from OCT, Henle fiber  
Figure 3: Relationship between the within subject standard deviation and the Coefficient of variation (CoV). Sw: Within subject standard deviation, Retinal Nerve Fiber Layer (RNFL), Ganglion Cell Layer (GCL), Inner Plexiform Layer (IPL), Inner Nuclear Layer (INL), Outer Plexiform Layer (OPL), Outer Nuclear Layer (ONL), Outer Segment (OS), and Retinal Pigment Epithelium (RPE). layer can appear either as a hyper-reflective or as a hypo-reflective structure [28; 30; 31; 32; 33]. As a consequence, the delineation of the OPL and ONL layers can be affected. Another report also shows that the agreement in the measurement values between horizontal and vertical scans are particularly bad for OPL and ONL layers [34]. The three most outer layers in the retina (RPE, OS and ONL) are thicker in the central sector and uniformly thinner in the other sectors. This makes it easier for the segmentation algorithm to identify and delineate these layers. The repeatability for RPE and OS is good as expected, but, for the ONL, the repeatability varies among the sectors. As mentioned earlier, the repeatability of ONL can be affected due to the difficulties of the segmentation algorithm in identifying and delineating the OPL-ONL layer.