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Compressed sensing MRI via two-stage reconstruction.
IEEE Trans Biomed Eng 2015; 62(1):110-8IT

Abstract

Compressed sensing (CS) has been applied to magnetic resonance imaging for the acceleration of data collection. However, existing CS techniques usually produce images with residual artifacts, particularly at high reduction factors. In this paper, we propose a novel, two-stage reconstruction scheme, which takes advantage of the properties of k-space data and under-sampling patterns that are useful in CS. In this algorithm, the under-sampled k-space data is segmented into low-frequency and high-frequency domains. Then, in stage one, using dense measurements, the low-frequency region of k-space data is faithfully reconstructed. The fully reconstituted low-frequency k-space data from the first stage is then combined with the high-frequency k-space data to complete the second stage reconstruction of the whole of k-space. With this two-stage approach, each reconstruction inherently incorporates a lower data under-sampling rate and more homogeneous signal magnitudes than conventional approaches. Because the restricted isometric property is easier to satisfy, the reconstruction consequently produces lower residual errors at each step. Compared with a conventional CS reconstruction, for the cases of cardiac cine, brain and angiogram imaging, the proposed method achieves a more accurate reconstruction with an improvement of 2-4 dB in peak signal-to-noise ratio respectively, using reduction factors of up to 6.

Authors

No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Evaluation Studies
Journal Article
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

25069108

Citation

Yang, Yang, et al. "Compressed Sensing MRI Via Two-stage Reconstruction." IEEE Transactions On Bio-medical Engineering, vol. 62, no. 1, 2015, pp. 110-8.
Yang Y, Liu F, Xu W, et al. Compressed sensing MRI via two-stage reconstruction. IEEE Trans Biomed Eng. 2015;62(1):110-8.
Yang, Y., Liu, F., Xu, W., & Crozier, S. (2015). Compressed sensing MRI via two-stage reconstruction. IEEE Transactions On Bio-medical Engineering, 62(1), pp. 110-8. doi:10.1109/TBME.2014.2341621.
Yang Y, et al. Compressed Sensing MRI Via Two-stage Reconstruction. IEEE Trans Biomed Eng. 2015;62(1):110-8. PubMed PMID: 25069108.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Compressed sensing MRI via two-stage reconstruction. AU - Yang,Yang, AU - Liu,Feng, AU - Xu,Wenlong, AU - Crozier,Stuart, Y1 - 2014/07/23/ PY - 2014/7/29/entrez PY - 2014/7/30/pubmed PY - 2015/9/9/medline SP - 110 EP - 8 JF - IEEE transactions on bio-medical engineering JO - IEEE Trans Biomed Eng VL - 62 IS - 1 N2 - Compressed sensing (CS) has been applied to magnetic resonance imaging for the acceleration of data collection. However, existing CS techniques usually produce images with residual artifacts, particularly at high reduction factors. In this paper, we propose a novel, two-stage reconstruction scheme, which takes advantage of the properties of k-space data and under-sampling patterns that are useful in CS. In this algorithm, the under-sampled k-space data is segmented into low-frequency and high-frequency domains. Then, in stage one, using dense measurements, the low-frequency region of k-space data is faithfully reconstructed. The fully reconstituted low-frequency k-space data from the first stage is then combined with the high-frequency k-space data to complete the second stage reconstruction of the whole of k-space. With this two-stage approach, each reconstruction inherently incorporates a lower data under-sampling rate and more homogeneous signal magnitudes than conventional approaches. Because the restricted isometric property is easier to satisfy, the reconstruction consequently produces lower residual errors at each step. Compared with a conventional CS reconstruction, for the cases of cardiac cine, brain and angiogram imaging, the proposed method achieves a more accurate reconstruction with an improvement of 2-4 dB in peak signal-to-noise ratio respectively, using reduction factors of up to 6. SN - 1558-2531 UR - https://www.unboundmedicine.com/medline/citation/25069108/Compressed_sensing_MRI_via_two_stage_reconstruction_ L2 - https://dx.doi.org/10.1109/TBME.2014.2341621 DB - PRIME DP - Unbound Medicine ER -