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In this work, we present a 3D single-particle tracking system that can apply tailored sampling patterns to selectively extract photons that yield the most information for particle localization. We demonstrate that off-center sampling at locations predicted by Fisher information utilizes photons most efficiently. When performing localization in a single dimension, optimized off-center sampling patterns gave doubled precision compared to uniform sampling. A ~20% increase in precision compared to uniform sampling can be achieved when a similar off-center pattern is used in 3D localization. Here, we systematically investigated the photon efficiency of different emission patterns in a diffraction-limited system and achieved higher precision than uniform sampling. The ability to maximize information from the limited number of photons demonstrated here is critical for particle tracking applications in biological samples, where photons may be limited.
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Efficient NUFFT backpropagation for stochastic sampling optimization
Optimization-based k-space sampling pattern design often involves the Jacobian matrix of non-uniform fast Fourier transform (NUFFT) operations. Previous works relying on auto-differentiation can be time-consuming and less accurate. This work proposes an approximation method using the relationship between exact non-uniform DFT (NDFT) and NUFFT, demonstrating improved results for the sampling pattern optimization problem.
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- Award ID(s):
- 1838179
- PAR ID:
- 10309645
- Date Published:
- Journal Name:
- Proceeedings International Society of Magnetic Resonance in Medicine
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Conference Paper:
- The DOI is not currently available.
