51 citations · 116 across the 11 of their papers we have counts for
12 papers
Dual-guided Hierarchical Edge Localization for Large-scale Optimal Transport Across Dimensions
Wenzhou Xia, Qiaoqiao Ding, Jingwei Liang +1
Optimal transport (OT) compares distributions and aligns datasets in machine learning, yet unregularized discrete OT requires a linear program with quadratically many transport var…
Diff-ANO: Towards Fast High-Resolution Ultrasound Computed Tomography via Conditional Consistency Models and Adjoint Neural Operators
Xiang Cao, Qiaoqiao Ding, Xinliang Liu +2
Ultrasound Computed Tomography (USCT) constitutes a nonlinear inverse problem with inherent ill-posedness that can benefit from regularization through diffusion generative priors.…
Dynamic PET Image Reconstruction via Non-negative INR Factorization
Chaozhi Zhang, Wenxiang Ding, Roy Y. He +2
The reconstruction of dynamic positron emission tomography (PET) images from noisy projection data is a significant but challenging problem. In this paper, we introduce an unsuperv…
Bi-modality medical images synthesis by a bi-directional discrete process matching method
Zhe Xiong, Qiaoqiao Ding, Xiaoqun Zhang
Recently, medical image synthesis gains more and more popularity, along with the rapid development of generative models. Medical image synthesis aims to generate an unacquired imag…
Multi-Scale Frequency-Enhanced Deep D-bar Method for Electrical Impedance Tomography
Xiang Cao, Qiaoqiao Ding, Xiaoqun Zhang
The regularized D-bar method is a popular method for solving Electrical Impedance Tomography (EIT) problems due to its efficiency and simplicity. It utilizes the low-pass truncated…
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport
Zhe Xiong, Qiaoqiao Ding, Xiaoqun Zhang
Finding a transformation between two unknown probability distributions from finite samples is crucial for modeling complex data distributions and performing tasks such as sample ge…
A Dataset-free Deep learning Method for Low-Dose CT Image Reconstruction
Qiaoqiao Ding, Hui Ji, Yuhui Quan +1
Low-dose CT (LDCT) imaging attracted a considerable interest for the reduction of the object's exposure to X-ray radiation. In recent years, supervised deep learning (DL) has been…
AHP-Net: adaptive-hyper-parameter deep learning based image reconstruction method for multilevel low-dose CT
Qiaoqiao Ding, Yuesong Nan, Hao Gao +1
Low-dose CT (LDCT) imaging is desirable in many clinical applications to reduce X-ray radiation dose to patients. Inspired by deep learning (DL), a recent promising direction of mo…
Low-Dose CT with Deep Learning Regularization via Proximal Forward Backward Splitting
Qiaoqiao Ding, Gaoyu Chen, Xiaoqun Zhang +2
Low dose X-ray computed tomography (LDCT) is desirable for reduced patient dose. This work develops image reconstruction methods with deep learning (DL) regularization for LDCT. Ou…
Statistical Image Reconstruction Using Mixed Poisson-Gaussian Noise Model for X-Ray CT
Qiaoqiao Ding, Yong Long, Xiaoqun Zhang +1
Statistical image reconstruction (SIR) methods for X-ray CT produce high-quality and accurate images, while greatly reducing patient exposure to radiation. When further reducing X-…
Image-domain multi-material decomposition for dual-energy CT based on correlation and sparsity of material images
Qiaoqiao Ding, Tianye Niu, Xiaoqun Zhang +1
Dual energy CT (DECT) enhances tissue characterization because it can produce images of basis materials such as soft-tissue and bone. DECT is of great interest in applications to m…
Dynamic SPECT reconstruction with temporal edge correlation
Qiaoqiao Ding, Martin Burger, Xiaoqun Zhang
In dynamic imaging, a key challenge is to reconstruct image sequences with high temporal resolution from strong undersampling projections due to a relatively slow data acquisition…