Retina vessel segmentation system based on combination of hessian matrix and region growing

Abstract

The invention discloses a retina vessel segmentation system based on combination of a hessian matrix and region growing. The retina vessel segmentation system comprises a retina image preprocessing unit which is used for extracting a retina image green channel and enhancing the extracted image to improve the contrast; a hessian matrix enhancement unit which re-enhances the image through the hessian matrix and extracts the vessel direction in the retina image; a connected domain classification unit which morphologically classifies the image enhanced by the hessian matrix so as to extract smallvessels; and a region growing unit which performs region growing on the classified image to connect the broken vessel structures in the image so as to enhance the segmentation image and improve the segmentation result. Vessel segmentation of the retina fundus image can be realized by the system, and the algorithm of combination of the hessian matrix and region growing is put forward by using the mode of combining the hessian matrix and region growing for aiming at the problem of appearance of breaking points in the segmentation result of the segmentation algorithm so that the situation of vessel breaking in the extracted image can be further improved and the accuracy of vessel segmentation can be enhanced.

Description

technical field [0001] The invention relates to the technical field of medical image processing, in particular to a retinal blood vessel segmentation system based on the combination of Hessian matrix and region growth. Background technique [0002] Retinal microvessels are the only ones in the human body that can directly observe deep microvessels without trauma, and changes in their state and structure can characterize the occurrence of various diseases including hypertension and diabetes. Therefore, the accurate segmentation of the fundus retinal vascular structure can be used to assist clinicians in the diagnosis and treatment of retinal diseases. Through the morphological analysis of retinal blood vessels, early diagnosis and prevention of some diseases are of great significance to the progress of clinical medicine. [0003] Due to the interference of factors such as uneven distribution of gray scale in retinal images, complex vascular structure, low contrast between tar...

AI Technical Summary

Problems solved by technology

[0004] The above method can extract most of the retinal blood vessels, but due to the limitation of the algorithm or the low contrast of the actual imaging, the segmentation results of the algorithm often show the phenomenon of broken blood vessels, which needs further improvement

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