Automated choroid segmentation in three-dimensional 1-μm wide-view OCT images with gradient and regional costs

Choroid thickness and volume estimated from optical coherence tomography (OCT) images have emerged as important metrics in disease management. This paper presents an automated three-dimensional (3-D) method for segmenting the choroid from 1 - ? m wide-view swept source OCT image volumes, including the Bruch’s membrane (BM) and the choroidal–scleral interface (CSI) segmentation. Two auxiliary boundaries are first detected by modified Canny operators and then the optical nerve head is detected and removed. The BM and the initial CSI segmentation are achieved by 3-D multiresolution graph search with gradient-based cost. The CSI is further refined by adding a regional cost, calculated from the wavelet-based gradual intensity distance. The segmentation accuracy is quantitatively evaluated on 32 normal eyes by comparing with manual segmentation and by reproducibility test. The mean choroid thickness difference from the manual segmentation is 19.16 ± 4.32 ?? ? m , the mean Dice similarity coefficient is 93.17 ± 1.30 % , and the correlation coefficients between fovea-centered volumes obtained on repeated scans are larger than 0.97.