Accelerated MRI

Accelerated MRI aims to significantly reduce scan times by acquiring incomplete k-space data and reconstructing high-quality images using advanced computational methods. Current research heavily utilizes deep learning, employing architectures like diffusion models, transformers, and convolutional neural networks, often integrated with physics-based constraints to improve reconstruction accuracy and robustness to noise. These advancements are crucial for improving patient comfort, enabling real-time imaging, and expanding the clinical applicability of MRI, particularly in applications like intraoperative imaging and high-resolution 3D scans. The field is also exploring self-supervised learning techniques to reduce reliance on fully-sampled training data.

Papers

April 17, 2022

Accelerated MRI With Deep Linear Convolutional Transform Learning
Hongyi Gu, Burhaneddin Yaman, Steen Moeller, Il Yong Chun, Mehmet Akçakaya
Deep Learning Convolutional Transformer Accelerated MRI Linear Representation Sparse Reconstruction

April 1, 2022

Data and Physics Driven Learning Models for Fast MRI -- Fundamentals and Methodologies from CNN, GAN to Attention and Transformers
Jiahao Huang, Yingying Fang, Yang Nan, Huanjun Wu, Yinzhe Wu, Zhifan Gao, Yang Li, Zidong Wang, Pietro Lio, Daniel Rueckert, Yonina C. Eldar, Guang Yang
Deep Learning Model Transformer Megatron Decepticons GAN Model CNN Network Physic Informed Fast Magnetic Resonance Imaging Accelerated MRI

March 9, 2022

Deep learning-based reconstruction of highly accelerated 3D MRI
Sangtae Ahn, Uri Wollner, Graeme McKinnon, Isabelle Heukensfeldt Jansen, Rafi Brada, Dan Rettmann, Ty A. Cashen, John Huston, J. Kevin DeMarco, Robert Y. Shih, Joshua D. Trzasko, Christopher J. Hardy, Thomas K. F. Foo
3D Brain Undersampled Magnetic Resonance Accelerated MRI Parallel Imaging Learning Based Reconstruction

February 6, 2022

Wave-Encoded Model-based Deep Learning for Highly Accelerated Imaging with Joint Reconstruction
Jaejin Cho, Borjan Gagoski, Taehyung Kim, Qiyuan Tian, Stephen Robert Frost, Itthi Chatnuntawech, Berkin Bilgic
Model Based Deep Learning Accelerated MRI Parallel Imaging Parallel Imaging Reconstruction

December 18, 2021

Equilibrated Zeroth-Order Unrolled Deep Networks for Accelerated MRI
Zhuo-Xu Cui, Jing Cheng, Qingyong Zhu, Yuanyuan Liu, Sen Jia, Kankan Zhao, Ziwen Ke, Wenqi Huang, Haifeng Wang, Yanjie Zhu, Dong Liang
Regularization Model MRI Reconstruction Accelerated MRI Deep Unrolled Unrolled Network

December 1, 2021

Highly accelerated MR parametric mapping by undersampling the k-space and reducing the contrast number simultaneously with deep learning
Yanjie Zhu, Haoxiang Li, Yuanyuan Liu, Muzi Guo, Guanxun Cheng, Gang Yang, Haifeng Wang, Dong Liang
Deep Learning K Space Mapping Approach Accelerated MRI Contrast Affecting Sequence Parameter Parametric Map