A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction

Liyan Sun; Zhiwen Fan; Xueyang Fu; Yue Huang; Xinghao Ding; John Paisley

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A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction

机译：深度信息共享网络，用于多对比度压缩传感MRI重建

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摘要

Compressed sensing (CS) theory can accelerate multi-contrast magnetic resonance imaging (MRI) by sampling fewer measurements within each contrast. However, conventional optimization-based reconstruction models suffer several limitations, including a stric

机译：压缩感测（CS）理论可以通过在每个对比度内采样较少的测量值来加速多对比度磁共振成像（MRI）。但是，传统的基于优化的重建模型存在一些局限性，包括严格的

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来源
《IEEE Transactions on Image Processing》 |2019年第12期|6141-6153|共13页
作者
Liyan Sun; Zhiwen Fan; Xueyang Fu; Yue Huang; Xinghao Ding; John Paisley;
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作者单位

School of Information Science and Engineering Xiamen University Xiamen China;

Department of Automation University of Science and Technology of China Hefei China;

School of;

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原文格式 PDF
正文语种 eng
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关键词
Transmitters; Receivers; Fading channels; Network coding; Output feedback; Numerical models; Nickel;

机译：发射器;接收器;衰落的频道;网络编码;输出反馈;数值模型;镍;
入库时间 2022-08-18 04:35:47

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专利

1. Simultaneous use of individual and joint regularization terms in compressive sensing: Joint reconstruction of multi-channel multi-contrast MRI acquisitions [J] . Kopanoglu Emre, Gungor Alper, Kilic Toygan, NMR in biomedicine . 2020,第4期

机译：同时使用个人和联合正则化术语压缩传感：多通道多对错MRI采集的联合重建
2. Multi-contrast reconstruction with Bayesian compressed sensing [J] . Berkin Bilgic, Vivek K Goyal, Elfar Adalsteinsson Magnetic Resonance in Medicine . 2011,第6期

机译：贝叶斯压缩感知的多对比度重建
3. Multi-contrast reconstruction with Bayesian compressed sensing [J] . BilgicB., GoyalV.K., AdalsteinssonE. Magnetic resonance in medicine: official journal of the Society of Magnetic Resonance in Medicine . 2011,第6期

机译：贝叶斯压缩感知的多对比度重建
4. Multi-channel, Multi-slice, and Multi-contrast Compressed Sensing MRI Using Weighted Forest Sparsity and Joint TV Regularization Priors [C] . Sumit Datta, Bhabesh Deka International Conference on Soft Computing for Problem Solving . 2019

机译：使用加权森林稀疏性和联合电视正则化前沿的多通道，多切片和多对比度压缩检测MRI
5. Image reconstructions of compressed sensing MRI with multichannel data [D] . Chang, Ching-Hua. 2016

机译：多通道数据的压缩传感MRI的图像重建
6. Reference-Driven Compressed Sensing MR Image Reconstruction Using Deep Convolutional Neural Networks without Pre-Training [O] . Di Zhao, Feng Zhao, Yongjin Gan 2020

机译：使用深度卷积神经网络的无预训练的参考驱动压缩感测MR图像重建
7. A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction [O] . Liyan Sun, Zhiwen Fan, Xueyang Fu, 2019

机译：用于多对比度压缩传感MRI重建的深度信息共享网络

A Deep Information Sharing Network for Multi-Contrast Compressed Sensing MRI Reconstruction

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