Abstract:

BACKGROUND: Fundus fluoresce in angiography can reflect the structure of retinal blood vessels, hemodynamic changes, disease management and related physiological changes and the structure of pathological changes, and has been widely used in the retina, choroid and optic nerve disease in the differential diagnosis.
OBJECTIVE: Through the analysis of the characteristics of retinal vessels and advantages and disadvantages of wavelet edge detection algorithm, to improve wavelet edge detection algorithm and to detect edge and measure width of retinal vessels.
METHODS: By the spline function structure transect wavelet, the wavelet filter ratio was obtained. Using the improved wavelet edge detection method, blood vessels initial edge of fundus fluorescence images was obtained. The edges of the initial margin refinement algorithm were detailed, and connected based on the fractal technology after the refinement edge. The noise reduction algorithm was used to eliminate the noise in the edge image, and pixel by a row of single-vessel edge was obtained. Using edge by two points between the vertical line of pixels, the actual diameter of blood vessels was obtained.
RESULTS AND CONCLUSION: This method well solved conventional routes edge detail and noise, with better continuity and less edge detection points. This method applied in the retina blood vessel width survey obtained similar diagnosis result to actual situation, which may help ophthalmologist's clinical diagnosis.