5 citations · 9 across the 5 of their papers we have counts for
5 papers
Image Denoising via Style Disentanglement
Jingwei Niu, Jun Cheng, Shan Tan
Image denoising is a fundamental task in low-level computer vision. While recent deep learning-based image denoising methods have achieved impressive performance, they are black-bo…
Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoising
Jun Cheng, Tao Liu, Shan Tan
Real-world single image denoising is crucial and practical in computer vision. Bayesian inversions combined with score priors now have proven effective for single image denoising b…
Unsupervised CT Metal Artifact Reduction by Plugging Diffusion Priors in Dual Domains
Xuan Liu, Yaoqin Xie, Songhui Diao +2
During the process of computed tomography (CT), metallic implants often cause disruptive artifacts in the reconstructed images, impeding accurate diagnosis. Several supervised deep…
Diffusion Probabilistic Priors for Zero-Shot Low-Dose CT Image Denoising
Xuan Liu, Yaoqin Xie, Jun Cheng +3
Denoising low-dose computed tomography (CT) images is a critical task in medical image computing. Supervised deep learning-based approaches have made significant advancements in th…
Quantification of Local Metabolic Tumor Volume Changes by Registering Blended PET-CT Images for Prediction of Pathologic Tumor Response
Sadegh Riyahi, Wookjin Choi, Chia-Ju Liu +8
Quantification of local metabolic tumor volume (MTV) chan-ges after Chemo-radiotherapy would allow accurate tumor response evaluation. Currently, local MTV changes in esophageal (s…