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Monitoring subtle choroidal thickness changes in the human eye delivers insight into the pathogenesis of various ocular diseases such as myopia and helps planning their treatment. However, a thorough evaluation of detection-performance is challenging as a ground truth for comparison is not available. Alternatively, an artificial ground truth can be generated by averaging the manual expert segmentations. This makes the ground truth very sensitive to ambiguities due to different interpretations by the experts. In order to circumvent this limitation, we present a novel validation approach that operates independently from a ground truth and is uniquely based on the common agreement between algorithm and experts. Utilizing an appropriate index, we compare the joint agreement of several raters with the algorithm and validate it against manual expert segmentation. To illustrate this, we conduct an observational study and evaluate the results obtained using our previously published registration-based method. In addition, we present an adapted state-of-the-art evaluation method, where a paired t-test is carried out after leaving out the results of one expert at the time. Automated and manual detection were performed on a dataset of 90 OCT 3D-volume stack pairs of healthy subjects between 8 and 18 years of age from Asian urban regions with a high prevalence of myopia.

Macular Telangiectasia Type 2 (MacTel2) is a disease of the retina leading to a gradual deterioration of central vision. At the onset of the disease a good visual acuity is present, which declines as the disease progresses to cause reading difficulties. In this paper, we present new insights on the vascular changes in MacTel2. We investigated whether MacTel2 progression correlates to changes in the thickness of the choroid. For this purpose, we apply a recently published registration-based approach to detect deviations in the choroid on a dataset of 45 MacTel2 patients. Between 2012 and 2016 these subjects and a control group were measured twice within variable intervals of time in the Moorfields Eye Hospital in the MacTel Natural History Observation and Registry Study. Our results show that in the MacTel2 group the thickness of the choroid increased while in the control group a decrease was noted. Manual expert segmentation and an automated state-of-the-art method were used to validate the results.

Recognizing significant temporal changes in the thickness of the choroid and retina at an early stage is a crucial factor in the prevention and treatment of ocular diseases such as myopia or glaucoma. Such changes are expected to be among the first indicators of pathological manifestations and are commonly dealt using segmentation-based approaches. However, segmenting the choroid is challenging due to low contrast, loss of signal and presence of artifacts in optical coherence tomography (OCT) images. In this paper, we present a novel method for early detection of choroidal changes based on piecewise rigid image registration. In order to adhere to the eye’s natural shape, the regularization enforces the local homogeneity of the transformations in nasal-temporal (x-) and superior-inferior (y-) direction by penalizing their radial differences. We restrict our transformation model to anterior-posterior (z-) direction, as we focus on juvenile myopia, which correlates to thickness changes in the choroid rather than to structural alterations. First, the precision of the method was tested on an OCT scan-rescan data set of 62 healthy Asian children, ages 7 to 13, from a population with a high prevalence of myopia. Furthermore, the accuracy of the method in recognizing synthetically induced changes in the data set was evaluated. Finally, the results were compared to those of manually annotated scans.

Detecting and monitoring changes in the human choroid play a crucial role in treating ocular diseases such as myopia. However, reliable segmentation of optical coherence tomography (OCT) images at the choroid-sclera interface (CSI) is notoriously difficult due to poor contrast, signal loss and OCT artefacts. In this paper we present blockwise registration of successive scans to improve stability also during complete loss of the CSI-signal. First, we formulated the problem as minimization of a regularized energy functional. Then, we tested our automated method for piecewise Intensity-based Choroidal rigid Registration using regularized block matching (ICR) on 20 OCT 3D-volume scan-rescan data set pairs. Finally, we used these data set pairs to determine the precision of our method, while the accuracy was determined by comparing our results with those using manually annotated scans.