Fast Segmentation Algorithm for Cystoid Macular Edema Based on Omnidirectional Wave Operator - Jing Liu; Shiliang Lou; Xiaodong Chen; Huaiyu Cai; Yi Wang (Applied Sciences, 2021)
Optical coherence tomography (OCT) is widely used in the field of ophthalmic imaging. The existing technology cannot automatically extract the contour of the OCT images of cystoid macular edema (CME) and can only evaluate the degree of lesions by detecting the thickness of the retina. To solve this problem, this paper proposes an automatic segmentation algorithm that can segment the CME in OCT images of the fundus quickly and accurately. This method firstly constructs the working environment by denoising and contrast stretching, secondly extracts the region of interest (ROI) containing CME according to the average gray distribution of the image, and then uses the omnidirectional wave operator to perform multidirectional automatic segmentation. Finally, the fused segmentation results are screened by gray threshold and position feature, and the contour extraction of CME is realized. The segmentation results of the proposed method on data set images are compared with those obtained by manual marking of experts. The accuracy, recall, Dice index, and F1-score are 88.8%, 75.0%, 81.1%, and 81.3%, respectively, with the average process time being 1.2 s. This algorithm is suitable for general CME image segmentation and has high robustness and segmentation accuracy.