Method and device of segmenting retinal vessels in fundus image
A technique for retinal blood vessels and fundus images, applied in image analysis, image enhancement, image data processing, etc., can solve problems such as inaccurate segmentation results and high complexity of retinal blood vessels, facilitate analysis and research, and solve inaccurate segmentation results, Precise effect of retinal vessels
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Embodiment 1
[0023] According to an embodiment of the present invention, a method embodiment of a method for segmenting retinal blood vessels in a fundus image is provided. It should be noted that the steps shown in the flow chart of the accompanying drawings can be performed on a computer such as a set of computer-executable instructions system, and, although a logical order is shown in the flowcharts, in some cases the steps shown or described may be performed in an order different from that shown or described herein.
[0024] figure 1 is a method for segmenting retinal blood vessels in fundus images according to an embodiment of the present invention, such as figure 1 As shown, the method includes the following steps:
[0025] Step S102, acquiring a fundus image.
[0026] Specifically, the fundus image may be obtained by taking a photo.
[0027] In step S104, the fundus image is processed based on the Hessian matrix to obtain a first retinal blood vessel map.
[0028] Specifically, ...
Embodiment 2
[0072] According to an embodiment of the present invention, a product embodiment of a device for segmenting retinal blood vessels in a fundus image is provided, Figure 4 is a device for segmenting retinal blood vessels in fundus images according to an embodiment of the present invention, such as Figure 4 As shown, the device includes an acquisition module 101 , a first processing module 103 , a second processing module 105 and a reconstruction module 107 .
[0073] Among them, the acquisition module 101 is used to acquire the fundus image; the first processing module 103 is used to process the fundus image based on the Hessian matrix to obtain the first retinal blood vessel map; the second processing module 105 is used to analyze the first retinal blood vessel The image is binarized to obtain a second retinal vessel map; the reconstruction module 107 is configured to reconstruct interrupted vessels in the second retinal vessel map to obtain a third retinal vessel map.
[00...
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