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Abstract #3485

Accelerated Echo Planar J-Resolved Spectroscopic Imaging in Prostate Cancer and A Hybrid Dictionary Learning-Total Variation Reconstruction

Ajin Joy1, Rajakumar Nagarajan1, Andres Saucedo1, Zohaib Iqbal1, Manoj K Sarma1, Neil E Wilson1, Ely R Felker1, Robert E Reiter2, Steven S Raman1, and M Albert Thomas1
1Radiological Sciences, University of California-Los Angeles, Los Angeles, CA, United States, 2Urology, University of California-Los Angeles, Los Angeles, CA, United States


Prospectively undersampled 5D echo-planar J-resolved spectroscopic imaging (EP-JRESI) data were acquired in 9 prostate cancer patients and 3 healthy controls. The 5D data was reconstructed using Dictionary learning (DL), Total Variation (TV), Perona-Malik (PM) and a hybrid DLTV method combining DL and TV. DLTV uses the gradient sparsity of TV and the learned dictionary-based sparsity of DL to further increase the transform sparsity of the data. The DLTV method unambiguously resolved 2D J-resolved peaks including myo-inositol, citrate, creatine, spermine and choline with an improved reconstruction that facilitates higher acceleration factors, leading to significant reduction in scan time.

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