Multi-shot sensitivity-encoded diffusion data recovery using structured low-rank matrix completion (MUSSELS)
نویسندگان
چکیده
منابع مشابه
Low-Rank Matrix Completion
While datasets are frequently represented as matrices, real-word data is imperfect and entries are often missing. In many cases, the data are very sparse and the matrix must be filled in before any subsequent work can be done. This optimization problem, known as matrix completion, can be made well-defined by assuming the matrix to be low rank. The resulting rank-minimization problem is NP-hard,...
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5 Minimization of the nuclear norm is often used as a surrogate, convex relaxation, for finding 6 the minimum rank completion (recovery) of a partial matrix. The minimum nuclear norm 7 problem can be solved as a trace minimization semidefinite programming problem (SDP ). 8 The SDP and its dual are regular in the sense that they both satisfy strict feasibility. Interior 9 point algorithms are th...
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ژورنال
عنوان ژورنال: Magnetic Resonance in Medicine
سال: 2016
ISSN: 0740-3194
DOI: 10.1002/mrm.26382