%PDF-1.4 % 5 0 obj << /S /GoTo /D (section.1) >> endobj 8 0 obj (1. Introduction) endobj 9 0 obj << /S /GoTo /D (subsection.1.1) >> endobj 12 0 obj (1.1. Trained dictionaries as sparsifying transforms) endobj 13 0 obj << /S /GoTo /D (subsection.1.2) >> endobj 16 0 obj (1.2. Likelihood estimate as data fidelity measure) endobj 17 0 obj << /S /GoTo /D (subsection.1.3) >> endobj 20 0 obj (1.3. Fast numerical algorithms for solving CS-MRI models) endobj 21 0 obj << /S /GoTo /D (subsection.1.4) >> endobj 24 0 obj (1.4. Organization) endobj 25 0 obj << /S /GoTo /D (section.2) >> endobj 28 0 obj (2. Proposed model) endobj 29 0 obj << /S /GoTo /D (subsection.2.1) >> endobj 32 0 obj (2.1. Sparse representation using trained dictionary) endobj 33 0 obj << /S /GoTo /D (subsection.2.2) >> endobj 36 0 obj (2.2. Likelihood estimate for the data consistency) endobj 37 0 obj << /S /GoTo /D (subsection.2.3) >> endobj 40 0 obj (2.3. Variational model for MR image reconstruction from undersampled data) endobj 41 0 obj << /S /GoTo /D (section.3) >> endobj 44 0 obj (3. Algorithm) endobj 45 0 obj << /S /GoTo /D (subsection.3.1) >> endobj 48 0 obj (3.1. A fast algorithm for solving the proposed model) endobj 49 0 obj << /S /GoTo /D (subsection.3.2) >> endobj 52 0 obj (3.2. Numerical algorithm and convergence analysis) endobj 53 0 obj << /S /GoTo /D (section.4) >> endobj 56 0 obj (4. Experimental results) endobj 57 0 obj << /S /GoTo /D (subsection.4.1) >> endobj 60 0 obj (4.1. Improvement on accuracy by using dictionaries) endobj 61 0 obj << /S /GoTo /D (subsection.4.2) >> endobj 64 0 obj (4.2. Improvement on robustness \(to parameter selection\) and efficiency) endobj 65 0 obj << /S /GoTo /D (subsection.4.3) >> endobj 68 0 obj (4.3. Robustness of dictionary training and reconstruction) endobj 69 0 obj << /S /GoTo /D (section.5) >> endobj 72 0 obj (5. Conclusion) endobj 73 0 obj << /S /GoTo /D (section*.1) >> endobj 76 0 obj (REFERENCES) endobj 77 0 obj << /S /GoTo /D [78 0 R /Fit ] >> endobj 80 0 obj << /Length 4003 /Filter /FlateDecode >> stream xڝZYsF~ׯ#X%`pe>XrVMe d f R8GO3џ?UFEI?7glESo|0 ?^,rX&$jvݹ+ NΕrPxVD7CJ_ݰ \0O+q3ٺ^Le}eS2|_c/]!}dW>mav{Tб女JDW1F$;B)۩y>6=3@7r(-Ѝ#ЋQYQ >SW'̀0NS
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