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Found 3 papers, 2 papers with code
3D U-NetR: Low Dose Computed Tomography Reconstruction via Deep Learning and 3 Dimensional Convolutions
In this paper, we introduced a novel deep learning-based reconstruction technique for low-dose CT imaging using 3 dimensional convolutions to include the sagittal information unlike the existing 2 dimensional networks which exploits correlation only in transverse plane.
Low-Dose CT Reconstruction Using Deep Generative Regularization Prior
In CT imaging, DL based methods try to learn a function that maps low-dose images to normal-dose images.
Self-Supervised Training For Low Dose CT Reconstruction
To reduce the dose level without compromising the image quality, low-dose CT reconstruction has been offered with the availability of compressed sensing based reconstruction methods.
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