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High spatiotemporal resolution fMRI using partial separability model

Issue title: Frontiers in Biomedical Engineering and Biotechnology – Proceedings of the 4th International Conference on Biomedical Engineering and Biotechnology, 18–21 August 2015, Shanghai, China

Guest editors: Feng Liu, Dong-Hoon Lee, Ricardo Lagoa and Sandeep Kumar

Article type: Research Article

Authors: Shi, Caiyuna | Xie, Guoxia; b; * | Zhang, Xiaoyonga; c | Su, Shia | Zhang, Yongqind | Zhang, Lijuana | Qiu, Benshengc | Liu, Xina; *

Affiliations: [a] Shenzhen Key Laboratory for MRI, Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology of Chinese Academy of Sciences, Shenzhen, China | [b] Beijing Center for Mathematics and Information Interdisciplinary Sciences, Beijing, China | [c] Centers for Biomedical Engineering, College of Information Science and Technology, University of Science and Technology of China, Hefei, China | [d] School of Information Science and Technology, Northwest University, Xian, China

Correspondence: [*] Address for correspondence: Guoxi Xie, Shenzhen Key Laboratory for MRI, Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology of Chinese Academy of Sciences, Shenzhen, China. Tel.: +86-0755-86392287; Fax: +86-0755-86392245; E-mail: gx.xie@siat.ac.cn. Xin Liu, Paul C. Lauterbur Research Center for Biomedical Imaging, Institute of Biomedical and Health Engineering, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Tel.: +86-0755-86392287; Fax: +86-0755-86392299; E-mail: xin.liu@siat.ac.cn.

Keywords: fMRI (function magnetic resonance imaging), partial separability (PS) model, sparse sampling, BOLD

DOI: 10.3233/BME-151442

Journal: Bio-Medical Materials and Engineering, vol. 26, no. s1, pp. S1439-S1446, 2015

Published: 2015
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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 mm3). 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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