High spatiotemporal resolution fMRI using partial separability model.
Caiyun Shi,Guoxi Xie,Xiaoyong Zhang,Xiaoyong Zhang,Shi Su,Yongqin Zhang,Lijuan Zhang,Bensheng Qiu,Xin Liu +8 more
TL;DR: (k-t) space data is sparsely acquired and reconstructed for BOLD fMRI using a partial separability (PS) model with a ℓ2-norm constraint, which achieves a high temporal resolution of 200 ms without compromising spatial resolution.
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Abstract: Blood oxygenation level dependent functional MRI (BOLD fMRI) requires repeatedly scanning the same region to capture neuronal activities, so the sampling data is very sparse along the temporal direction, which offers an opportunity to accelerate the fMRI. In this paper, (k-t) space data is sparsely acquired and reconstructed for BOLD fMRI using a partial separability (PS) model with a l2-norm constraint. The proposed approach achieves a high temporal resolution of 200 ms without compromising spatial resolution (3.5 × 3.5 × 4.0 mm(3)). A simulation based on the EPI data with the right finger tapping experiment demonstrates that the proposed method can realize high spatiotemporal fMRI with accurate reconstruction of the activation regions from highly undersampled data. Meanwhile, preliminary in vivo experiment results also demonstrate the potential application of the proposed method in fMRI.
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Citations
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An integrated analysis of the extended hippocampal system across species
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- 01 Jan 2017
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