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Abstract #0051

Improved Dynamic Contrast Enhanced MRI Using Low Rank with Joint Sparsity Reconstruction

Jichang Zhang1, Faisal Najeeb2, Xinpei Wang1, Pengfei Xu1, Hammad Omer2, Penny Gowland 3, Sue Francis3, Paul Glover3, Richard Bowtell3, and Chengbo Wang1
1SPMIC, The University of Nottingham Ningbo China, Ningbo, China, 2COMSATS University Islamabad, Islamabad, Pakistan, 3SPMIC, The University of Nottingham, Nottingham, United Kingdom

This work presents a free breathing Dynamic Contrast Enhanced MRI (DCE-MRI) reconstruction method called L+S (Low rank plus sparse) with joint sparsity, which improved dynamic contrast performance through integrating an additional temporal Fast Fourier Transform (FFT) constraint by extending the standard L+S decomposition method. Fast Composite Splitting Algorithm (FCSA) is implemented to solve the L+S optimization problem in proposed method, and to minimize the computation complexity from joint sparsity constraints. The proposed method achieved high spatial-temporal resolution, high reconstruction efficiency and improved dynamic contrast simultaneously when comparing with other methods in reconstructing a simulated phantom dataset and a DCE-MRI dataset.

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