Method for automatically identifying and distinguishing eye fundus images

Abstract

The invention discloses a method for automatically identifying and distinguishing eye fundus images. The method comprises the following steps: obtaining black and white or colored eye fundus image pictures by using eye fundus photographic equipment, and storing the black and white or colored eye fundus image pictures according to a left eye or a right eye; dividing the eye fundus image of the left eye or the right eye into seven regions, which are respectively a first region-optic disk region, a second region-macular region, a third region- macular temporal region, a fourth region- area temporalis superior, a fifth region- area temporalis inferior, a sixth region- superior nasal region and a seventh region- inferior nasal region; and automatically judging that the collected eye fundus image belongs to one of the seven eye fundus regions through the computer graphics according to the optic disk, macular and vascular network information in the eye fundus image. The method disclosed by the invention is used for introducing automatic computer image identification into the processing of the images of the seven eye fundus regions, and extracting feature structures of different eye fundus regions to serve as reference for automatically locating and collecting the eye fundus image, and providing a brand new manner for researchers or film reading doctors to research and read the images of the seven eye fundus regions, so as to greatly improve the film reading efficiency and reduce the error probability.

Description

technical field [0001] The invention relates to a fundus image image processing technology based on computer image recognition technology, in particular to a fundus image automatic recognition partition method. Background technique [0002] Fundus retinal images can be fully and clearly obtained by fundus photography equipment. Due to the different angles of the camera when taking pictures, or because of the needs of lesion locations, fundus images of different fundus regions are often obtained. The existing partitioning methods are usually divided into nasal and retinal regions centered on the optic disc. In the upper, lower nasal, superior temporal and inferior temporal areas, researchers or doctors study the fundus images, and diagnose and grade related diseases according to the characteristics and severity of lesions in each fundus area. When studying, it is necessary to first determine the area to which the obtained fundus image belongs. Under the condition that the fun...

AI Technical Summary

Problems solved by technology

[0002] Fundus retinal images can be fully and clearly obtained by fundus photography equipment. Due to the different angles of the camera when taking pictures, or because of the needs of lesion locations, fundus images of different fundus regions are often obtained. The existing partitioning methods are usually divided into nasal and retinal regions centered on the optic disc. In the upper, lower nasal, superior temporal and inferior temporal areas, researchers or doctors study the fundus images, and diagnose and grade related diseases according to the characteristics and severity of lesions in each fundus area. When studying, it is necessary to first determine the area to which the obtained fundus image belongs. Under the condition that the fundus image is simply divided into four areas, the images of a single case involve at least dozens of images, the amount of film reading is very large, and it is easy to confuse

[0003] In order to further accurately divide the lesions, which is beneficial to determine the condition and obtain effective treatment, the current trend is to further accurately subdivide the fundus area, and the result of subdivision is to further increase the number of fundus images obtained in a geometric progression, which will provide follow-up Reading the film caused great difficulties and also hindered the development of the discipline

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