OBJECTIVEUsing the algorithm on the layered structure of the retina and quantitative analysis of the automatic segmentation technique is the key to the early diagnosis of glaucoma and other retinopathy on optical coherence tomography. Existing methods require high quality image and have low reliability. This paper used the improved complex nonlinear diffuse filtering and other methods to solve this problem.

METHODSThis paper includes algorithm such as automatic threshold, improved complex nonlinear diffusion filtering, morphological operations and peak detection. Use the method for the segmentation of 20 retinal layers images which acquired on the self-builder OCT system, the boundary of inner limiting membrane(ILM), outer nuclear layer(ONL), the photoreceptor segments(IS/ OS) and the RPE_ChCap layer are detected accurately. At last, the photoreceptor layer thickness is measured.

RESULTSThe results of segmentation and measurement are good corresponded with expert manual segmentation and measurements, retinal foveal measurements data is consistent with Zeiss Stratus OCT central retinal thickness 212+/-20 micro m.

CONCLUSIONThe algorithm proposed is prospective applied to clinical diagnosis of retinal diseases.