Method and system for identifying grid change holes in wide-area fundus images based on deep learning
A deep learning, fundus image technology, applied in the field of medical image processing, can solve the problems of inability to detect and evaluate, time-consuming inspection, visual impairment, etc., and achieve the effect of reducing training expenditure, efficient disease evaluation, and reducing burden
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Embodiment 1
[0041] Such as figure 1 As shown, the present embodiment provides a method for identifying grid change holes in a wide-area fundus image based on deep learning, including the following steps:
[0042] S1. Input the wide-area fundus image into the convolutional neural network, and judge whether there is lattice degeneration or hole in the peripheral retina in the wide-area fundus image;
[0043] S2. When it is judged that there is lattice degeneration or hole in the peripheral retina in the wide-area fundus image, the location of the lattice degeneration or the hole in the wide-area fundus image is located using a significant area algorithm.
[0044] In step S1, the convolutional neural network can be used to accurately and efficiently analyze the wide-area fundus image to determine whether there is a lesion on the image; in step S2, the salient area algorithm (Saliency Map) can be used to locate the lesion on the image. This can assist ophthalmologists to interpret patients' ...
Embodiment 2
[0073] like image 3 As shown, this embodiment provides a system for identifying grid change holes in wide-area fundus images based on deep learning, including:
[0074] A judging module, configured to input the wide-area fundus image into the convolutional neural network, and judge whether there is a lattice-like degeneration or hole in the peripheral retina in the wide-area fundus image;
[0075] The positioning module is used to locate the grid-like degeneration or hole in the wide-area fundus image by using the salient area algorithm when it is judged that there is a grid-like degeneration or hole in the surrounding retina in the wide-area fundus image;
[0076] The judging module can accurately and efficiently analyze the wide-area fundus image through the convolutional neural network, and judge whether there is a lesion on the image; the positioning module can locate the location of the lesion on the image through the salient area algorithm (Saliency Map), which can assi...
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