Abstract: A method for establishing a three-dimensional ultrasound image blind denoising model and a use thereof include: adding a speckle noise to three-dimensional biological structure images of a same size and without speckle noise to obtain a training data set; establishing a three-dimensional denoising network based on an encoding-decoding structure, wherein the encoding structure is used to obtain N feature maps of a three-dimensional input image and perform a downsampling to obtain feature maps of different scales; the decoding structure is used to take a feature map obtained by the encoding structure as an input and reconstruct a three-dimensional image without speckle noise through upsampling; dividing the encoding-decoding structure into a plurality of stages by a downsampling structure and an upsampling structure; training the three-dimensional denoising network using the training data set to obtain a three-dimensional ultrasound image blind denoising model.

Abstract: A method for establishing a three-dimensional ultrasound image blind denoising model and a use thereof include: adding a speckle noise to three-dimensional biological structure images of a same size and without speckle noise to obtain a training data set; establishing a three-dimensional denoising network based on an encoding-decoding structure, wherein the encoding structure is used to obtain N feature maps of a three-dimensional input image and perform a downsampling to obtain feature maps of different scales; the decoding structure is used to take a feature map obtained by the encoding structure as an input and reconstruct a three-dimensional image without speckle noise through upsampling; dividing the encoding-decoding structure into a plurality of stages by a downsampling structure and an upsampling structure; training the three-dimensional denoising network using the training data set to obtain a three-dimensional ultrasound image blind denoising model.