1.7k citations · 1.7k across the 6 of their papers we have counts for
6 papers
Diffusion Prior Regularized Iterative Reconstruction for Low-dose CT
Wenjun Xia, Yongyi Shi, Chuang Niu +2
Computed tomography (CT) involves a patient's exposure to ionizing radiation. To reduce the radiation dose, we can either lower the X-ray photon count or down-sample projection vie…
Blind CT Image Quality Assessment Using DDPM-derived Content and Transformer-based Evaluator
Yongyi Shi, Wenjun Xia, Ge Wang +1
Lowering radiation dose per view and utilizing sparse views per scan are two common CT scan modes, albeit often leading to distorted images characterized by noise and streak artifa…
Task-based Assessment of Deep Networks for Sinogram Denoising with A Transformer-based Observer
Yongyi Shi, Ge Wang, Xuanqin Mou
A variety of supervise learning methods are available for low-dose CT denoising in the sinogram domain. Traditional model observers are widely employed to evaluate these methods. H…
Enabling Competitive Performance of Medical Imaging with Diffusion Model-generated Images without Privacy Leakage
Yongyi Shi, Wenjun Xia, Chuang Niu +2
Deep learning methods have impacted almost every research field, demonstrating notable successes in medical imaging tasks such as denoising and super-resolution. However, the prere…
Lesion classification by model-based feature extraction: A differential affine invariant model of soft tissue elasticity
Weiguo Cao, Marc J. Pomeroy, Zhengrong Liang +9
The elasticity of soft tissues has been widely considered as a characteristic property to differentiate between healthy and vicious tissues and, therefore, motivated several elasti…
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…