1 code implementation • 5 Jun 2023 • Chi Ding, Qingchao Zhang, Ge Wang, Xiaojing Ye, YunMei Chen
We propose a novel Learned Alternating Minimization Algorithm (LAMA) for dual-domain sparse-view CT image reconstruction.
no code implementations • 8 Apr 2022 • Wanyu Bian, Qingchao Zhang, Xiaojing Ye, YunMei Chen
In this paper, we propose a novel deep-learning model for joint reconstruction and synthesis of multi-modal MRI using incomplete k-space data of several source modalities as inputs.
no code implementations • 2 Oct 2021 • Wanyu Bian, YunMei Chen, Xiaojing Ye, Qingchao Zhang
In this model, the learnable regularization function contains a task-invariant common feature encoder and task-specific learner represented by a shallow network.
no code implementations • 27 Apr 2021 • Qingchao Zhang, Mehrdad Alvandipour, Wenjun Xia, Yi Zhang, Xiaojing Ye, YunMei Chen
We propose a provably convergent method, called Efficient Learned Descent Algorithm (ELDA), for low-dose CT (LDCT) reconstruction.
no code implementations • 1 Oct 2020 • Qingchao Zhang, Coy D. Heldermon, Corey Toler-Franklin
We present an algorithm for multi-scale tumor (chimeric cell) detection in high resolution slide scans.
no code implementations • 22 Jul 2020 • Yunmei Chen, Hongcheng Liu, Xiaojing Ye, Qingchao Zhang
We propose a general learning based framework for solving nonsmooth and nonconvex image reconstruction problems.
no code implementations • 15 Mar 2020 • Qingchao Zhang, Xiaojing Ye, Hongcheng Liu, Yun-Mei Chen
Optimization algorithms for solving nonconvex inverse problem have attracted significant interests recently.
no code implementations • 17 Nov 2019 • Qingchao Zhang, Yun-Mei Chen
Variational method and deep learning method are two mainstream powerful approaches to solve inverse problems in computer vision.