Academic Journal
Dynamic Sparse Mask Spatial-Frequency System Matrix Compression for Accelerated Reconstruction in Narrowband Magnetic Particle Imaging.
| Τίτλος: | Dynamic Sparse Mask Spatial-Frequency System Matrix Compression for Accelerated Reconstruction in Narrowband Magnetic Particle Imaging. |
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| Συγγραφείς: | Bian Z, Chen Z, Li J, Zhu T, Shi G, Zhang H, Li G, An Y, Tian J |
| Πηγή: | IEEE transactions on bio-medical engineering [IEEE Trans Biomed Eng] 2026 Aug; Vol. 73 (8), pp. 2940-2952. |
| Τύπος έκδοσης: | Journal Article |
| Γλώσσα: | English |
| Στοιχεία περιοδικού: | Publisher: Institute Of Electrical And Electronics Engineers Country of Publication: United States NLM ID: 0012737 Publication Model: Print Cited Medium: Internet ISSN: 1558-2531 (Electronic) Linking ISSN: 00189294 NLM ISO Abbreviation: IEEE Trans Biomed Eng Subsets: MEDLINE |
| Imprint Name(s): | Publication: New York, NY : Institute Of Electrical And Electronics Engineers Original Publication: New York, IEEE Professional Technical Group on Bio-Medical Engineering. |
| Ιατρικοί όροι (MeSH): | Magnetic Particle Imaging*/methods , Image Processing, Computer-Assisted*/methods , Data Compression*/methods, Signal-To-Noise Ratio ; Algorithms ; Phantoms, Imaging ; Humans |
| Περίληψη: | Objective: Narrowband magnetic particle imaging (MPI), owing to its inherently high signal-to-noise ratio (SNR), has shown strong potential for enabling large-field-of-view (FOV) scanners suitable for human-scale imaging. System-matrix (SM)-based reconstruction can effectively suppress image blurring and negative artifacts. However, enlarging the FOV greatly increases the SM size, leading to prohibitive memory usage and prolonged reconstruction time. Methods: To address this challenge, we propose a Spatial-Frequency System Matrix (SF-SM) approach that exploits the sparse representation of calibration responses in the discrete cosine transform (DCT) domain to achieve substantial matrix reduction. Subsequently, a Dynamic Sparse Mask (DSM) strategy is introduced to retain the most informative spatial-frequency components: a global prior mask removes consistently low-contribution frequency components, while a signal-driven mask derived from the measured harmonic image captures object-dependent spectral characteristics. Their intersection serves to extract a task-adaptive specific SM that retains informative components and suppresses noise-dominated high-frequency terms. Results: Extensive validation using simulation studies, a public dataset, and an in-house narrowband MPI scanner demonstrates that the proposed approach compresses the SM to approximately 1% of its original size in the best cases, accelerates reconstruction by nearly two orders of magnitude, and maintains or even enhances image quality relative to the Raw-SM. Conclusion: The proposed DSM-based SF-SM enables substantial SM compression and highly efficient reconstruction while preserving image quality. Significance: DSM-based SF-SM provides an efficient and scalable solution for accelerating narrowband MPI reconstruction, particularly in large-FOV systems and applications requiring real-time imaging performance. |
| Entry Date(s): | Date Created: 20260527 Date Completed: 20260810 Latest Revision: 20260929 |
| Update Code: | 20260930 |
| DOI: | 10.1109/TBME.2026.3697397 |
| PMID: | 42202196 |
| Βάση Δεδομένων: | MEDLINE |
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