133 citations · 167 across the 12 of their papers we have counts for
8 papers · 1 filter
From Data Completeness to Data Sufficiency: A Task-Driven Imaging Framework for Intraoperative CBCT under Quality-Time-Dose Trade-offs
Yi Jia, Rongjun Ge, Yang Chen +2
Mobile C-arm cone-beam computed tomography (CBCT) has been widely used for real-time intraoperative 3D imaging. However, current practice often mechanically applies the fan-beam CT…
Patch-Based Denoising Diffusion Probabilistic Model for Sparse-View CT Reconstruction
Wenjun Xia, Wenxiang Cong, Ge Wang
Sparse-view computed tomography (CT) can be used to reduce radiation dose greatly but is suffers from severe image artifacts. Recently, the deep learning based method for sparse-vi…
Low-Dose CT Using Denoising Diffusion Probabilistic Model for 20 Speedup
Wenjun Xia, Qing Lyu, Ge Wang
Low-dose computed tomography (LDCT) is an important topic in the field of radiology over the past decades. LDCT reduces ionizing radiation-induced patient health risks but it also…
Unsupervised PET Reconstruction from a Bayesian Perspective
Chenyu Shen, Wenjun Xia, Hongwei Ye +5
Positron emission tomography (PET) reconstruction has become an ill-posed inverse problem due to low-count projection data, and a robust algorithm is urgently required to improve i…
One Network to Solve Them All: A Sequential Multi-Task Joint Learning Network Framework for MR Imaging Pipeline
Zhiwen Wang, Wenjun Xia, Zexin Lu +5
Magnetic resonance imaging (MRI) acquisition, reconstruction, and segmentation are usually processed independently in the conventional practice of MRI workflow. It is easy to notic…
Provably Convergent Learned Inexact Descent Algorithm for Low-Dose CT Reconstruction
Qingchao Zhang, Mehrdad Alvandipour, Wenjun Xia +3
We propose a provably convergent method, called Efficient Learned Descent Algorithm (ELDA), for low-dose CT (LDCT) reconstruction. ELDA is a highly interpretable neural network arc…