Automatic Segmentation of Layers in Chorio-Retinal Complex Using Graph-based Method for Ultra-Speed 1.7 MHz Wide Field Swept Source FDML Optical Coherence Tomography

The posterior segment of the human eye complex contains two discrete microstructure and vasculature network systems, namely, the retina and choroid. We present a single segmentation framework technique for segmenting the entire layers present in the chorio-retinal complex of the human eye using optical coherence tomography (OCT) images. This automatic program is based on the graph theory method. This single program is capable of segmenting seven layers of the retina and choroid scleral interface. The graph theory was utilized to find the probability matrix and subsequent boundaries of different layers. The program was also implemented to segment angiographic maps of different chorio-retinal layers using "segmentation matrices." The method was tested and successfully validated on OCT images from six normal human eyes as well as eyes with non-exudative age-related macular degeneration (AMD). The thickness of microstructure and microvasculature for different layers located in the chorio-retinal segment of the eye was also generated and compared. A decent efficiency in terms of processing time, sensitivity, and accuracy was observed compared to the manual segmentation and other existing methods. The proposed method automatically segments whole OCT images of chorio-retinal complex with augmented probability maps generation in OCT volume dataset. We have also evaluated the segmentation results using quantitative metrics such as Dice coefficient and Hausdorff distance This method realizes a mean descent Dice similarity coefficient (DSC) value of 0.82 (range, 0.816-0.864) for RPE and CSI layer.