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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/79423

    Title: Combining parallel detection of proton echo planar spectroscopic imaging (PEPSI) measurements with a data-consistency constraint improves SNR
    Authors: Tsai, Shang-Yueh;Hsu, Yi-Cheng;Chu, Ying-Hua;Kuo, Wen-Jui;Lin, Fa-Hsuan
    Contributors: 應物所
    Keywords: proton echo planar spectroscopy imaging;data consistency;SNR;regularization
    Date: 2015-10
    Issue Date: 2015-11-25 16:36:41 (UTC+8)
    Abstract: One major challenge of MRSI is the poor signal-to-noise ratio (SNR), which can be improved by using a surface coil array. Here we propose to exploit the spatial sensitivity of different channels of a coil array to enforce the k-space data consistency (DC) in order to suppress noise and consequently to improve MRSI SNR. MRSI data were collected using a proton echo planar spectroscopic imaging (PEPSI) sequence at 3 T using a 32-channel coil array and were averaged with one, two and eight measurements (avg-1, avg-2 and avg-8). The DC constraint was applied using a regularization parameter λ of 1, 2, 3, 5 or 10. Metabolite concentrations were quantified using LCModel. Our results show that the suppression of noise by applying the DC constraint to PEPSI reconstruction yields up to 32% and 27% SNR gain for avg-1 and avg-2 data with λ = 5, respectively. According to the reported Cramer–Rao lower bounds, the improvement in metabolic fitting was significant (p < 0.01) when the DC constraint was applied with λ ≥ 2. Using the DC constraint with λ = 3 or 5 can minimize both root-mean-square errors and spatial variation for all subjects using the avg-8 data set as reference values. Our results suggest that MRSI reconstructed with a DC constraint can save around 70% of scanning time to obtain images and spectra with similar SNRs using λ = 5.
    Relation: NMR in Biomedicine, 刊登於網路, 1-10
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1002/nbm.3425
    DOI: 10.1002/nbm.3425
    Appears in Collections:[應用物理研究所 ] 期刊論文

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