OCT image denoising method and device based on annular adversarial generative network

An image and ring technology, applied in biological neural network models, image enhancement, image analysis, etc., can solve the problem of unsatisfactory denoising effect of OCT images, and achieve the effect of reducing time-consuming, improving denoising effect and improving efficiency.

Pending Publication Date: 2019-10-29
PING AN TECH (SHENZHEN) CO LTD
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AI Technical Summary

Problems solved by technology

[0004] The present invention provides an OCT image denoising method, device and medium based on a ring-based confrontation generation network to solve the problem of unsatisfactory denoising effect on OCT images using a conditional confrontational neural network model in the prior art

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  • OCT image denoising method and device based on annular adversarial generative network
  • OCT image denoising method and device based on annular adversarial generative network
  • OCT image denoising method and device based on annular adversarial generative network

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Embodiment Construction

[0034] Embodiments of the present invention will be described below with reference to the accompanying drawings. Those skilled in the art would recognize that the described embodiments can be modified in various ways or combinations thereof without departing from the spirit and scope of the invention. Accordingly, the drawings and description are illustrative in nature and serve only to explain the invention, rather than to limit the scope of protection of the claims. Also, in this specification, the drawings are not drawn to scale, and like reference numerals denote like parts.

[0035] figure 1 It is a schematic flow chart of the OCT image denoising method based on the ring confrontation generation network of the present invention, as figure 1 As shown, the OCT image denoising method based on ring confrontation generation network of the present invention comprises the following steps:

[0036] Step S1, obtaining the OCT image to be denoised;

[0037] Step S2, inputting t...

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Abstract

The invention belongs to the technical field of artificial intelligence, and discloses an OCT image denoising method and device based on an annular generative adversarial network, and the method comprises the steps: obtaining a to-be-denoised OCT image; inputting the to-be-denoised OCT image into a trained annular adversarial generative network model; and outputting a denoised OCT image through the annular adversarial generative network model. According to the method, the OCT image is denoised through the annular adversarial generative network model, and the high-noise OCT image is effectivelyconverted into the clear OCT image, so that a doctor can read the image or use the OCT image for software analysis. Moreover, the limitation that training data must be paired in denoising applicationin previous deep learning is avoided, and acquisition of a large amount of data for training is facilitated, so that the denoising effect of the model is improved.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to an OCT image denoising method and device based on a ring confrontation generation network. Background technique [0002] Optical coherence tomography (OCT), as an emerging optical diagnostic technology, can be used to examine delicate parts such as eyes, and help patients diagnose and treat glaucoma, corneal diseases, and senile macula earlier and more accurately Lesions etc. However, OCT images are prone to noise, which poses a huge challenge for doctors to read images or use them for software analysis. Generally, high-noise images need to be denoised first, and then handed over to doctors for reading or software analysis. At present, the technology for image denoising processing includes two directions: computer vision and deep learning. The computer vision method takes BM3D as an example, and there are problems such as too long processing time. With t...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06N3/04G06N3/08
CPCG06N3/08G06T2207/10101G06T2207/20081G06T2207/20084G06N3/045G06T5/70
Inventor 郭晏吕彬吕传峰谢国彤
Owner PING AN TECH (SHENZHEN) CO LTD
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