Image noise reduction method and application thereof
An image noise reduction and image technology, which is applied in the field of image scanning, can solve the problems that affect the doctor's diagnosis of the disease, MRI image noise, etc., achieve good edge details and improve image quality
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[0064] Step 1: Build a self-correcting convolutional neural network framework. This application replaces the original convolutional module with a U-net network. figure 2 Self-correcting convolution shown;
[0065] Step 2: Use the L1 norm between the noise reduction result obtained after the low-quality magnetic resonance image in the paired data passes through the network designed in Step 1 and the high-quality as the loss function;
[0066] Step 3: Use the optimizer to optimize the loss function in step 2, iteratively optimize the parameters in the network designed in step 1, and finally make the loss function in step 2 converge;
[0067] Step 4: Give the network noise and noise-free data. The noisy data passes through the network to obtain the L1 norm between the denoised data and the noise-free data as the loss function. Use the optimizer to optimize it to change Step 1 Design the parameters in the network, and finally get the mapping of the network para...
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