ULTRA-Net: An Efficient and Interpretable Deep Network for Low-Dose CT Images Denoising

This publication has 33 references indexed in Scilit:

• CTformer: convolution-free Token2Token dilated vision transformer for low-dose CT denoising
  Physics in Medicine & Biology, 2023
• Deep Convolutional Dictionary Learning for Image Denoising
  2021
• Deep learning for tomographic image reconstruction
  Nature Machine Intelligence, 2020
• Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction
  Nature Machine Intelligence, 2019
• A Tutorial on Sparse Signal Reconstruction and Its Applications in Signal Processing
  Circuits, Systems, and Signal Processing, 2018
• Learned Convolutional Sparse Coding
  2018
• Low‐dose CT for the detection and classification of metastatic liver lesions: Results of the 2016 Low Dose CT Grand Challenge
  Medical Physics, 2017
• U-Net: Convolutional Networks for Biomedical Image Segmentation
  2015
• Improving abdomen tumor low-dose CT images using a fast dictionary learning based processing
  Physics in Medicine & Biology, 2013
• Computed Tomography — An Increasing Source of Radiation Exposure
  New England Journal of Medicine, 2007