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Positive‐contrast susceptibility imaging based on first‐order primal‐dual optimization
Author(s) -
Shi Caiyun,
Cheng Jing,
Xie Guoxi,
Su Shi,
Chang Yuchou,
Chen Hanwei,
Liu Xin,
Wang Haifeng,
Liang Dong
Publication year - 2019
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.27791
Subject(s) - contrast (vision) , imaging phantom , visualization , computer science , algorithm , thresholding , kernel (algebra) , iterative reconstruction , conjugate gradient method , artificial intelligence , mathematical optimization , mathematics , nuclear medicine , image (mathematics) , medicine , combinatorics
Purpose To achieve faster reconstruction and better imaging quality of positive‐contrast MRI based on the susceptibility mapping by incorporating a primal‐dual (PD) formulation. Methods The susceptibility‐based positive contrast MR technique was applied to estimate arbitrary magnetic susceptibility distributions of the metallic devices using a kernel deconvolution algorithm with a regularized ℓ 1 minimization. The regularized positive‐contrast inversion problem and its PD formulation were derived. The visualization of the positive contrast and convergence behavior of the PD algorithm were compared with those of the nonlinear conjugate gradient algorithm, fast iterative soft‐thresholding algorithm, and alternating direction method of multipliers. These methods were tested and validated on computer simulations and phantom experiments. Results The PD approach could provide a faster reconstruction time compared with other methods. Experimental results showed that the PD algorithm could achieve comparable or even better visualization and accuracy of the metallic interventional devices in positive‐contrast imaging with different SNRs and orientations to the B 0 field. Conclusion A susceptibility‐based positive‐contrast imaging technique by PD algorithm was proposed. The PD approach has more superior performance than other algorithms in terms of reconstruction time and accuracy for imaging the metallic interventional devices.