Two stage contour evolution for automatic segmentation of choroid and cornea in OCT images

Abstract

Enhanced depth imaging optical coherence tomography (EDI OCT) enables visualization of deeper layers of retina, the segmentation of which can help in the diagnosis of many ophthalmic diseases. Though, a wide variety of segmentation algorithms are available for clinical practice in retinal analysis, segmentation of cornea and choroid are still done manually due to the lack of automated segmentation tools. This paper proposes a multilevel contour evolution approach for segmenting various layers of cornea and choroid. Rotating kernel transformation (RKT) is applied for enhancing the edges followed by two stage contour evolution for detecting edges. Choroid/cornea thickness obtained using our algorithm is compared with manual segmented images traced by ophthalmologists. The algorithm showed good consistency and high correlation with manual segmentation. The results, provided separately for choroid and cornea segmentation prove the efficiency of the proposed method.