Convolutional neural network medical CT image denoising method based on residual error learning
A convolutional neural network and CT image technology, applied in the field of medical image denoising, to achieve the effect of improving image denoising ability, good pertinence, and improving training efficiency
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[0065] The invention will be specifically explained below in conjunction with the drawings
[0066] The specific steps of the convolutional neural network medical CT image denoising method based on residual learning of the present invention are as follows:
[0067] Step 1) Construct a medical CT image model;
[0068] The CT image model is mainly composed of two parts, both the effective human tissue reflection signal and the invalid noise signal, while the noise signal includes multiplicative noise and additive noise. Among them, additive noise is more important to CT images than multiplicative noise. The impact is very small. Due to the consideration of multiplicative noise, the general model s(x,y) of CT electrical signal is expressed as:
[0069] s(x,y)=r(x,y)n(x,y) (1)
[0070] Among them, (x, y) represents the horizontal and vertical coordinates of the image, r(x, y) represents the noise-free signal, and n(x, y) represents the multiplying noise.
[0071] Step 2) Construct a neural...
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