High Efficient Reconstruction of Single-Shot Magnetic Resonance T2 Mapping Through Overlapping Echo Detachment and DenseNet

被引:0
作者
Wang, Chao [1 ]
Wu, Yawen [1 ]
Ding, Xinghao [1 ]
Huang, Yue [1 ]
Cai, Congbo [1 ,2 ]
机构
[1] Xiamen Univ, Sch Informat Sci & Engn, Fujian Key Lab Sensing & Comp Smart City, Xiamen 361005, Fujian, Peoples R China
[2] Xiamen Univ, Dept Elect Sci, Fujian Prov Key Lab Plasma & Magnet Resonance, Xiamen 361005, Fujian, Peoples R China
来源
NEURAL INFORMATION PROCESSING (ICONIP 2018), PT VI | 2018年 / 11306卷
基金
中国国家自然科学基金;
关键词
Magnetic resonance imaging (MRI); Single-shot T-2 mapping; Reconstruction; Deep learning; DenseNet;
D O I
10.1007/978-3-030-04224-0_35
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Rapid and quantitative magnetic resonance T-2 imaging plays an important role in medical imaging field. However, the existing quantitative T-2 mapping method are usually time-consuming and sensitive to motion artifacts. Recently, a novel single-shot quantitative parameter mapping method based on overlapped-echo detachment technique has been proposed by us, but an efficient reconstruction algorithm is necessary. In this paper, a multi-stage DenseNet was utilized to reconstruct single-shot T-2 mapping efficiently. The contributions of the paper mainly include the following aspects. First, an end-to-end neural network is proposed, which can directly obtain the reconstructed images without any secondary processing. Second, DenseNet was introduced into the reconstruction network to better reuse the features. Third, a weighted Euclidean loss function is proposed, which can be better used for image reconstruction.
引用
收藏
页码:408 / 418
页数:11
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