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Iterative 3D projection reconstruction of (23) Na data with an (1) H MRI constraint.
Magn Reson Med. 2014 May; 71(5):1720-32.MR

Abstract

PURPOSE

To increase the signal-to-noise ratio (SNR) and to reduce artifacts in non-proton magnetic resonance imaging (MRI) by incorporation of a priori information from (1) H MR data in an iterative reconstruction.

METHODS

An iterative reconstruction algorithm for 3D projection reconstruction (3DPR) is presented that combines prior anatomical knowledge and image sparsity under a total variation (TV) constraint. A binary mask (BM) is used as an anatomical constraint to penalize non-zero signal intensities outside the object. The BM&TV method is evaluated in simulations and in MR measurements in volunteers.

RESULTS

In simulated BM&TV brain data, the artifact level was reduced by 20% while structures were well preserved compared to gridding. SNR maps showed a spatially dependent SNR gain over gridding reconstruction, which was up to 100% for simulated data. Undersampled 3DPR (23) Na MRI of the human brain revealed an SNR increase of 29 ± 7%. Small anatomical structures were reproduced with a mean contrast loss of 14%, whereas in TV-regularized iterative reconstructions a loss of 66% was found.

CONCLUSION

The BM&TV algorithm allows reconstructing images with increased SNR and reduced artifact level compared to gridding and performs superior to an iterative reconstruction using an unspecific TV constraint only.

Authors+Show Affiliations

Department of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.No affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info availableNo affiliation info available

Pub Type(s)

Journal Article

Language

eng

PubMed ID

23754674

Citation

Gnahm, Christine, et al. "Iterative 3D Projection Reconstruction of (23) Na Data With an (1) H MRI Constraint." Magnetic Resonance in Medicine, vol. 71, no. 5, 2014, pp. 1720-32.
Gnahm C, Bock M, Bachert P, et al. Iterative 3D projection reconstruction of (23) Na data with an (1) H MRI constraint. Magn Reson Med. 2014;71(5):1720-32.
Gnahm, C., Bock, M., Bachert, P., Semmler, W., Behl, N. G., & Nagel, A. M. (2014). Iterative 3D projection reconstruction of (23) Na data with an (1) H MRI constraint. Magnetic Resonance in Medicine, 71(5), 1720-32. https://doi.org/10.1002/mrm.24827
Gnahm C, et al. Iterative 3D Projection Reconstruction of (23) Na Data With an (1) H MRI Constraint. Magn Reson Med. 2014;71(5):1720-32. PubMed PMID: 23754674.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Iterative 3D projection reconstruction of (23) Na data with an (1) H MRI constraint. AU - Gnahm,Christine, AU - Bock,Michael, AU - Bachert,Peter, AU - Semmler,Wolfhard, AU - Behl,Nicolas G R, AU - Nagel,Armin M, Y1 - 2013/06/10/ PY - 2012/09/24/received PY - 2013/05/07/revised PY - 2013/05/07/accepted PY - 2013/6/12/entrez PY - 2013/6/12/pubmed PY - 2014/12/19/medline KW - anatomical prior knowledge KW - iterative reconstruction KW - non-proton MRI KW - projection reconstruction KW - sodium MRI SP - 1720 EP - 32 JF - Magnetic resonance in medicine JO - Magn Reson Med VL - 71 IS - 5 N2 - PURPOSE: To increase the signal-to-noise ratio (SNR) and to reduce artifacts in non-proton magnetic resonance imaging (MRI) by incorporation of a priori information from (1) H MR data in an iterative reconstruction. METHODS: An iterative reconstruction algorithm for 3D projection reconstruction (3DPR) is presented that combines prior anatomical knowledge and image sparsity under a total variation (TV) constraint. A binary mask (BM) is used as an anatomical constraint to penalize non-zero signal intensities outside the object. The BM&TV method is evaluated in simulations and in MR measurements in volunteers. RESULTS: In simulated BM&TV brain data, the artifact level was reduced by 20% while structures were well preserved compared to gridding. SNR maps showed a spatially dependent SNR gain over gridding reconstruction, which was up to 100% for simulated data. Undersampled 3DPR (23) Na MRI of the human brain revealed an SNR increase of 29 ± 7%. Small anatomical structures were reproduced with a mean contrast loss of 14%, whereas in TV-regularized iterative reconstructions a loss of 66% was found. CONCLUSION: The BM&TV algorithm allows reconstructing images with increased SNR and reduced artifact level compared to gridding and performs superior to an iterative reconstruction using an unspecific TV constraint only. SN - 1522-2594 UR - https://www.unboundmedicine.com/medline/citation/23754674/Iterative_3D_projection_reconstruction_of__23__Na_data_with_an__1__H_MRI_constraint_ L2 - https://doi.org/10.1002/mrm.24827 DB - PRIME DP - Unbound Medicine ER -