1.7k citations · 2.4k across the 6 of their papers we have counts for
6 papers
Structure-sensitive Multi-scale Deep Neural Network for Low-Dose CT Denoising
Chenyu You, Qingsong Yang, Hongming Shan +8
Computed tomography (CT) is a popular medical imaging modality in clinical applications. At the same time, the x-ray radiation dose associated with CT scans raises public concerns…
3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network
Hongming Shan, Yi Zhang, Qingsong Yang +5
Low-dose computed tomography (CT) has attracted a major attention in the medical imaging field, since CT-associated x-ray radiation carries health risks for patients. The reduction…
Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss
Qingsong Yang, Pingkun Yan, Yanbo Zhang +5
In this paper, we introduce a new CT image denoising method based on the generative adversarial network (GAN) with Wasserstein distance and perceptual similarity. The Wasserstein d…
CT Image Reconstruction in a Low Dimensional Manifold
Wenxiang Cong, Ge Wang, Qingsong Yang +3
Regularization methods are commonly used in X-ray CT image reconstruction. Different regularization methods reflect the characterization of different prior knowledge of images. In…
CT Image Denoising with Perceptive Deep Neural Networks
Qingsong Yang, Pingkun Yan, Mannudeep K. Kalra +1
Increasing use of CT in modern medical practice has raised concerns over associated radiation dose. Reduction of radiation dose associated with CT can increase noise and artifacts,…
Attenuation map reconstruction from TOF PET data
Qingsong Yang, Wenxiang Cong, Ge Wang
To reconstruct a radioactive tracer distribution with positron emission tomography (PET), the background attenuation correction is needed to eliminate image artifacts. Recent resea…