High Efficient Reconstruction of Single-shot T2 Mapping from OverLapping-Echo Detachment Planar Imaging Based on Deep Residual Network

17 Aug 2017 • Congbo Cai • Yiqing Zeng • Chao Wang • Shuhui Cai • Jun Zhang • Zhong Chen • Xinghao Ding • Jianhui Zhong

Purpose: An end-to-end deep convolutional neural network (CNN) based on deep residual network (ResNet) was proposed to efficiently reconstruct reliable T2 mapping from single-shot OverLapping-Echo Detachment (OLED) planar imaging. Methods: The training dataset was obtained from simulations carried out on SPROM software developed by our group... (read more)

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METHOD	TYPE
Average Pooling	Pooling Operations
ReLU	Activation Functions
1x1 Convolution	Convolutions
Batch Normalization	Normalization
Bottleneck Residual Block	Skip Connection Blocks
Global Average Pooling	Pooling Operations
Residual Block	Skip Connection Blocks
Kaiming Initialization	Initialization
Max Pooling	Pooling Operations
Residual Connection	Skip Connections
Convolution	Convolutions
ResNet	Convolutional Neural Networks

METHOD

TYPE

Average Pooling