Image Denoising

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  Low Dose CT Image Denoising using A Generative Adversarial Network with Wasserstein Distance and Perceptual Loss

  • Published on: April, 2018
  • Mannudeep K. Kalra, Hengyong Yu, Member, Xuanqin Mou, Pingkun Yan, Qingsong Yang, Senior Member, Yi Zhang Memb...
  • Code Available

  The continuous development and extensive use of CT in medical practice has raised a public concern over the associated radiation dose to the patient. ...

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  Probabilistic Noise2Void: Unsupervised Content-Aware Denoising

  • Published on: February, 2020
  •  Tomas Vicar,  Florian Jug, Alexander Krull
  • Code Available

  Convolutional Neural Network algorithm is leading technic for image denoising. Usually CNNs are used on pair of images, but it is impractical and diff ...

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  Sharpness-aware Low dose CT denoising using conditional generative adversarial network

  • Published on: September, 2017
  • Xin Yi, Paul Babyn
  • Code Available

  Due to radiation restrictions, Low Dose Computed Tomography (LDCT) has offered tremendous benefits in clinical applications. In this model an adversar ...

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  3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network

  • Published on: February, 2019
  • Hongming Shan, Mannudeep K. Kalra, Uwe Kruger, Yi Zhang, Ge Wang, Qingsong Yang, Wenxiang Cong, Ling Sun
  • Code Available

  Since CT-associated x-ray radiation poses health risks to patients, low-dose computed tomography (CT) has gotten a lot of attention in the medical ima ...

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  Iterative Low-Dose CT Reconstruction with Priors Trained by Artificial Neural Network

  • Published on: November, 2017
  •  Georges El Fakhri,  Kyungsang Kim, Dufan Wu, Quanzheng Li
  • Code Available

  To reduce radiation risk for patients, Dose reduction in computed tomography (CT) is essential. Iterative reconstruction algorithms turn out to be use ...