no code implementations • 14 Jun 2023 • Ruiyang Zhao, Xi Peng, Varun A. Kelkar, Mark A. Anastasio, Fan Lam
We present a novel method that integrates subspace modeling with an adaptive generative image prior for high-dimensional MR image reconstruction.
no code implementations • 28 Mar 2022 • Ruiyang Zhao, Zhao He, Tao Wang, Suhao Qiu, Pawel Herman, Yanle Hu, Chencheng Zhang, Dinggang Shen, Bomin Sun, Guang-Zhong Yang, Yuan Feng
Here we proposed a convolutional long short-term memory (Conv-LSTM) based recurrent neural network (RNN), or ConvLR, to reconstruct interventional images with golden-angle radial sampling.
no code implementations • 23 Sep 2021 • Ruiyang Zhao, Yuxin Zhang, Burhaneddin Yaman, Matthew P. Lungren, Michael S. Hansen
Deep learning techniques have emerged as a promising approach to highly accelerated MRI.
1 code implementation • 8 Sep 2021 • Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael S. Hansen, Matthew P. Lungren
Improving speed and image quality of Magnetic Resonance Imaging (MRI) via novel reconstruction approaches remains one of the highest impact applications for deep learning in medical imaging.