A fused LASSO operator for fast 3D magnetic particle imaging reconstruction.

Yimeng Li, Hui Hui, Jie Tian, Jie He, Peng Zhang

Journal: Physics in medicine and biology 2024;69(13):

PMID: 38815602

Abstract

Magnetic particle imaging (MPI) is a promising imaging modality that leverages the nonlinear magnetization behavior of superparamagnetic iron oxide nanoparticles to determine their concentration distribution. Previous optimization models with multiple regularization terms have been proposed to achieve high-quality MPI reconstruction, but these models often result in increased computational burden, particularly for dense gridding 3D fields of view. In order to achieve faster reconstruction speeds without compromising reconstruction quality, we have developed a novel fused LASSO operator, total sum-difference (TSD), which effectively captures the sparse and smooth priors of MPI images.Through an analysis-synthesis equivalence strategy and a constraint smoothing strategy, the TSD regularized model was solved using the fast iterative soft-thresholding algorithm (FISTA). The resulting reconstruction method, TSD-FISTA, boasts low computational complexity and quadratic convergence rate over iterations.Experimental results demonstrated that TSD-FISTA required only 10% and 37% of the time to achieve comparable or superior reconstruction quality compared to commonly used fused LASSO-based alternating direction method of multipliers and Tikhonov-based algebraic reconstruction techniques, respectively.TSD-FISTA shows promise for enabling real-time 3D MPI reconstruction at high frame rates for large fields of view.

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Address: School of Engineering Medicine and School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, People's Republic of China.; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing 100191, People's Republic of China.; Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100005, People's Republic of China.; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, People's Republic of China.; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China.; National Key Laboratory of Kidney Diseases, Beijing 100853, People's Republic of China.; School of Engineering Medicine and School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, People's Republic of China.; Key Laboratory of Big Data-Based Precision Medicine (Beihang University), Ministry of Industry and Information Technology of China, Beijing 100191, People's Republic of China.; CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, People's Republic of China.; National Key Laboratory of Kidney Diseases, Beijing 100853, People's Republic of China.

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