Automated vessel centerline extraction and diameter measurement in OCT Angiography

Optical Coherence Tomography Angiography (OCTA) is a non-invasive imaging technique that enables the visualization of perfused vasculature in vivo. In ophthalmology, it allows the physician to monitor diseases affecting the vascular networks of the retina such as agerelated macular degeneration or diabetic retinopathy. Due to the complexity of the vasculature in the retina, it is of interest to automatically extract vascular parameters which describe the condition of the vessels. Suitable parameters could improve the diagnosis and the treatment during the course of therapy. We present an automated algorithm to compute the diameters of the vessels in en face OCTA images. After segmenting the images, the vessel centerline was computed using a thinning algorithm. The centerline was refined by detecting invalid pixels such as spurs and by continuing the centerline until the ends of the vessels. Lastly, the diameter was computed by dilating a discrete circle at the position of the centerline or by measuring the distance between both borders of the vessels. The developed algorithms were applied to in vivo images of human eyes. Certainly, no ground truth was available. Hence, a plausibility check was performed by comparing the measured diameters of two different layers of the retina (Superficial Vascular Complex (SVC) and Deep Vascular Complex (DVC)). Each layer exhibits a different characteristic vasculature. The algorithm clearly reflected the differences from both retinal layers. The measured diameters demonstrate that the DVC consists of more capillaries and considerably smaller vessels compared to the SVC. The presented method enables automated analysis of the retinal vasculature and forms thereby the basis for monitoring diseases influencing the vasculature of the retina. The validation of the method using an artificial ground truth is still needed.