OCT Image Denoising Method Based on Dense Connections and Generative Adversarial Networks

A dense connection and image technology, applied in the field of OCT image denoising, can solve problems such as poor effect and different targets, achieve high use value, high speed and performance, and enhance the effect of reuse and transmission

Active Publication Date: 2022-02-11
CENT SOUTH UNIV
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Problems solved by technology

Although super-resolution, anti-aliasing and denoising problems are to restore the details of the image as much as possible, the goals of these tasks are different, and there are great differences between different types of training images. For the denoising problem of OCT images ,not effectively
Although in natural images and other medical fields, deep learning based on adversarial networks has been researched and applied in image restoration, but currently there is no denoising method based on deep learning applied in the field of OCT.

Method used

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  • OCT Image Denoising Method Based on Dense Connections and Generative Adversarial Networks
  • OCT Image Denoising Method Based on Dense Connections and Generative Adversarial Networks
  • OCT Image Denoising Method Based on Dense Connections and Generative Adversarial Networks

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Embodiment 1

[0061] 1) Generate the denoising effect of the model

[0062] The denoising effect of this model is as follows Figure 5 As shown, compared with the reference image, it can be seen that the model can remove noise better, and preserve the boundary information of the retina level as much as possible, so that the image has higher definition and quality. Using the peak signal-to-noise ratio and structural similarity as the evaluation index of the whole image, the similarity between the predicted image and the reference image in the spatial domain can be calculated. Peak signal-to-noise ratio and structural similarity are more traditional evaluation indicators. We further use the frequency domain absolute error as the evaluation index according to the characteristics of noise in the frequency domain, and calculate the predicted image and reference image in the frequency domain. similarity. On the other hand, since the OCT image has a large area as the background area, the area of...

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Abstract

The invention discloses an OCT image denoising method based on dense connection and generation confrontation network, which belongs to the technical field of image restoration. According to the characteristics of noise randomness, the invention adopts a multi-frame registration method to synthesize a reference image, so that the network can learn The mapping relationship between the noise image and the reference image; the step of synthesizing noise can effectively expand the diversity of speckle noise and synthesize new sample data; use the multi-scale features of the network for dense fusion to enhance effective features with fewer parameters The repeated use and transfer of the image; the way of confrontation generation network is used to ensure the overall perceptual quality of the image; the trained generative model can directly process noisy OCT images of any resolution, with high speed and performance, and has a high clinical value. use value.

Description

technical field [0001] The invention belongs to the technical field of image restoration, and in particular relates to an OCT image denoising method based on dense connection and generation confrontation network. Background technique [0002] Optical coherence tomography (Optical Coherence Tomography, OCT) is a non-invasive, reproducible, 3D fundus tissue imaging technology, which has many applications in ophthalmology. Quantitative analysis of OCT images of eye tissue is helpful It is used in the diagnosis of glaucoma, age-related macular degeneration, diabetic retinal edema and other eye diseases by doctors. OCT is a high-resolution imaging technology that is easily affected by the objective acquisition environment, and the imaging beam is scattered and coherently superimposed by intraocular tissues multiple times, forming speckle noise, which is a common phenomenon in OCT images. Several properties of speckle noise make its removal challenging. Different from ordinary a...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06T11/00
CPCG06T5/002G06T11/008G06T2207/10101G06T2207/30041
Inventor 陈再良曾梓洋沈海澜郑贤先戴培山欧阳平波
Owner CENT SOUTH UNIV
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