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10.1002/mrm.25168 http://scihub22266oqcxt.onion/10.1002/mrm.25168 C4051394!4051394 !24496655     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=24496655 &cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Magn+Reson+Med 2014 ; 71 (4 ): 1349-57 Nephropedia Template TP {{tp|p=24496655 |t=2014. A subspace approach to high-resolution spectroscopic imaging |pdf=|usr=}}{{24496655 }} gab.com Text A subspace approach to high-resolution spectroscopic imaging JO: Magn Reson Med http://www.kidney.de/pget.php?&tw=1&pmid=24496655 #FOAvip PURPOSE: To accelerate spectroscopic imaging using sparse sampling of (k,t)-space and subspace (or low-rank) modeling to enable high-resolution metabolic imaging with good signal-to-noise ratio. METHODS: The proposed method, called SPectroscopic Imaging by exploiting spatiospectral CorrElation, exploits a unique property known as partial separability of spectroscopic signals. This property indicates that high-dimensional spectroscopic signals reside in a very low-dimensional subspace and enables special data acquisition and image reconstruction strategies to be used to obtain high-resolution spatiospectral distributions with good signal-to-noise ratio. More specifically, a hybrid chemical shift imaging/echo-planar spectroscopic imaging pulse sequence is proposed for sparse sampling of (k,t)-space, and a low-rank model-based algorithm is proposed for subspace estimation and image reconstruction from sparse data with the capability to incorporate prior information and field inhomogeneity correction. RESULTS: The performance of the proposed method has been evaluated using both computer simulations and phantom studies, which produced very encouraging results. For two-dimensional spectroscopic imaging experiments on a metabolite phantom, a factor of 10 acceleration was achieved with a minimal loss in signal-to-noise ratio compared to the long chemical shift imaging experiments and with a significant gain in signal-to-noise ratio compared to the accelerated echo-planar spectroscopic imaging experiments. CONCLUSION: The proposed method, SPectroscopic Imaging by exploiting spatiospectral CorrElation, is able to significantly accelerate spectroscopic imaging experiments, making high-resolution metabolic imaging possible. Twit Text FOAVip A subspace approach to high-resolution spectroscopic imaging ????Magn Reson Med http://www.kidney.de/pget.php?&tw=1&pmid=24496655 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=24496655 #FOAvip English Wikipedia <ref>{{Cite pmid|24496655 }}</ref> A subspace approach to high-resolution spectroscopic imaging #MMPMID24496655 Lam F ; Liang ZP Magn Reson Med 2014[Apr]; 71 (4 ): 1349-57 PMID24496655 show ga PURPOSE: To accelerate spectroscopic imaging using sparse sampling of (k,t)-space and subspace (or low-rank) modeling to enable high-resolution metabolic imaging with good signal-to-noise ratio. METHODS: The proposed method, called SPectroscopic Imaging by exploiting spatiospectral CorrElation, exploits a unique property known as partial separability of spectroscopic signals. This property indicates that high-dimensional spectroscopic signals reside in a very low-dimensional subspace and enables special data acquisition and image reconstruction strategies to be used to obtain high-resolution spatiospectral distributions with good signal-to-noise ratio. More specifically, a hybrid chemical shift imaging/echo-planar spectroscopic imaging pulse sequence is proposed for sparse sampling of (k,t)-space, and a low-rank model-based algorithm is proposed for subspace estimation and image reconstruction from sparse data with the capability to incorporate prior information and field inhomogeneity correction. RESULTS: The performance of the proposed method has been evaluated using both computer simulations and phantom studies, which produced very encouraging results. For two-dimensional spectroscopic imaging experiments on a metabolite phantom, a factor of 10 acceleration was achieved with a minimal loss in signal-to-noise ratio compared to the long chemical shift imaging experiments and with a significant gain in signal-to-noise ratio compared to the accelerated echo-planar spectroscopic imaging experiments. CONCLUSION: The proposed method, SPectroscopic Imaging by exploiting spatiospectral CorrElation, is able to significantly accelerate spectroscopic imaging experiments, making high-resolution metabolic imaging possible. |*Algorithms [MESH] |*Data Interpretation, Statistical [MESH] |*Models, Statistical [MESH] |Brain/*metabolism [MESH] |Computer Simulation [MESH] |Magnetic Resonance Spectroscopy/*methods [MESH]A subspace approach to high-resolution spectroscopic imaging (epmc).pdf DeepDyve Pubget Overpricing