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Fundus OCT image classification method and computer readable storage medium

A classification method and image technology, applied in image analysis, computer parts, computing, etc., can solve problems such as complicated steps and limited accuracy, and achieve the effect of improving accuracy, increasing nonlinearity, and optimizing computing resources.

Pending Publication Date: 2020-10-30
SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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AI Technical Summary

Problems solved by technology

[0006] In order to solve the problem that the traditional method relies on initial feature selection, the steps are complicated and the accuracy is limited, and the deep learning method requires a large number of image annotations, it provides a classification method for fundus OCT images and a computer-readable storage medium

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  • Fundus OCT image classification method and computer readable storage medium
  • Fundus OCT image classification method and computer readable storage medium
  • Fundus OCT image classification method and computer readable storage medium

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Embodiment Construction

[0031] In order to make the technical problems, technical solutions and beneficial effects to be solved by the embodiments of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0032] It should be noted that when an element is referred to as being “fixed” or “disposed on” another element, it may be directly on the other element or be indirectly on the other element. When an element is referred to as being "connected to" another element, it can be directly connected to the other element or indirectly connected to the other element. In addition, the connection can be used for both fixing function and circuit communication function.

[0033] It is to be understood that the terms "length", "width", "top", "bottom", "front"...

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Abstract

The invention provides a fundus OCT image classification method and a computer readable storage medium. The fundus OCT image classification method comprises: S1, acquiring fundus OCT images to be classified; S2, classifying the fundus OCT images to be classified by adopting a trained convolutional neural network model, wherein the convolutional neural network model is of a serial structure; and S3, obtaining a classification result of the fundus OCT image to be classified. Fundus OCT images are classified by adopting a convolutional neural network model of a serial structure, the precision ofa classification network is effectively improved through iterative training based on a convolutional neural network framework, and end-to-end retinal lesion OCT image classification can be realized under the condition of insufficient data annotation / small-scale data sets.

Description

technical field [0001] The invention relates to the technical field of OCT image classification, in particular to a method for classifying fundus OCT images and a computer-readable storage medium. Background technique [0002] The macular area is an important area of ​​the retina, which is related to visual functions such as color vision and fine vision. Once lesions occur in the macular area, vision will be negatively affected. Retinal imaging technology can help doctors understand the pathogenesis of diseases such as age-related macular degeneration, diabetic retinopathy and macular hole. Early detection of these diseases can also further prevent more serious vision loss. play an important role. Optical coherence tomography (OCT) is a non-invasive diagnostic technique. It uses the concept of interferometry to create a cross-sectional view within the retina, enabling optical ranging with micron-level resolution, and has become an indispensable imaging tool in the diagnos...

Claims

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Application Information

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IPC IPC(8): G06T7/00G06T5/00G06N3/04G06N3/08G06K9/62
CPCG06T7/0012G06N3/08G06T2207/30041G06N3/045G06F18/2414G06T5/73
Inventor 董宇涵成垦张凯李志德
Owner SHENZHEN GRADUATE SCHOOL TSINGHUA UNIV
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