Generative Adversarial Networks for Noise Reduction in Low-Dose CT.
IEEE Transactions on Medical Imaging(2017)
摘要
Noise is inherent to low-dose CT acquisition. We propose to train a convolutional neural network (CNN) jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise. A generator CNN was trained to transform low-dose CT images into routine-dose CT images using voxelwise loss minimization. An adversarial discriminator CNN was simultaneously trained...
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关键词
Computed tomography,Generators,Noise reduction,Convolution,Training,Transforms,Calcium
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