An adaptive self-guided wavelet convolutional neural network with compound loss for low-dose CT denoising

Excessive X-ray radiation during CT imaging can bring potential health risks. Reducing the radiation dose will increase the noise and artifacts of the reconstructed image and affect the doctor's early diagnosis. In order to improve the image quality of LDCT, we propose a deep learning method for LDCT image denoising.