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Focus image classification and identification method based on fundus image

A fundus image and recognition method technology, applied in the field of medical image processing, can solve the problems of small diseased tissues that cannot be detected in time, difficult, hidden in blood vessels, etc., and achieve the effect of improving capture ability, accurate results, and broad application prospects

Pending Publication Date: 2022-07-29
CHONGQING UNIV OF POSTS & TELECOMM
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AI Technical Summary

Problems solved by technology

[0004] In traditional lesion analysis, many small diseased tissues cannot be found in time, especially in the process of fundus detection
Most fundus images are based on blood vessel segmentation images, and the lesions are often hidden in the blood vessels. At this time, it is very difficult to detect only by visual acuity

Method used

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  • Focus image classification and identification method based on fundus image
  • Focus image classification and identification method based on fundus image
  • Focus image classification and identification method based on fundus image

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Embodiment Construction

[0036] The embodiments of the present invention are described below through specific specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the drawings provided in the following embodiments are only used to illustrate the basic idea of ​​the present invention in a schematic manner, and the following embodiments and features in the embodiments can be combined with each other without conflict.

[0037] see Figure 1 to Figure 3 , In the method for classifying and identifying images of lesions based on fundus images provided by the present invention, the firs...

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Abstract

The invention relates to a focus image classification and identification method based on fundus images, and belongs to the field of medical image processing. According to the method, a YOLOv5 network structure and a target frame are fused in a weighted mode to form a frame, data sets of collected eye fundus images are deepened through a Mosaic method, the deepened image data sets and loss function training and image classification are combined, then the images enter the target frame weighted fusion frame, and finally binary images of different eye fundus images are output according to classification probabilities. And outputting the focus binary images in a classified manner. According to the method, the focus feature extraction capability of the network model is improved.

Description

technical field [0001] The invention belongs to the field of medical image processing, and relates to a lesion image classification and identification method based on fundus images. Background technique [0002] At present, fundus examination is mainly performed manually by doctors using fundus ophthalmoscopy, fundus imaging technology, fundus camera imaging and mutual interference technology of light. The fundus camera can clearly capture the main tissue structures on the retina. In the color fundus image, the blood vessels are most widely distributed on the retina and appear as a dark red reticular structure, which and optic nerve fibers enter the retina from the optic disc area. The optic disc is characterized by a disc-like structure with clear borders and highlights. In addition, if the color of the fundus image is darker, it can be called the macular area. The macular area is an oval depression, and the depressed part is called the fovea. The fovea is the most sensi...

Claims

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Application Information

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IPC IPC(8): G06V10/764G06V10/80G06V10/82G06K9/62G06N3/04G06N3/08
CPCG06N3/08G06N3/045G06F18/254G06F18/24G06F18/253
Inventor 周雨周贺凯袁慧郭恒睿刘姝杭曹恩苓
Owner CHONGQING UNIV OF POSTS & TELECOMM
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