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Reconstruction Algorithms in Multifocal Image Scanning Microscopy
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DOI：10.1002/lpor.71408.png)
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Abstract
En 中文
Breakthroughs in super-resolution fluorescence microscopy have greatly advanced the life sciences. Multifocal image scanning microscopy (MISM) preserves the resolution advantages of image scanning microscopy (ISM) while substantially increasing imaging speed through parallel excitation and detection. It achieves a favorable balance among resolution, signal-to-noise ratio, and phototoxicity. However, the parallelized hardware architecture of MISM also introduces physical limitations, such as inter-pinhole crosstalk. As a result, algorithmic progress becomes a key factor for correcting image degradation and unlocking the super-resolution potential of MISM. This paper provides a systematic review of recent advances in MISM reconstruction algorithms. We first outline the physical implementation and system classification of MISM, and analyze the major challenges encountered during reconstruction. Building on this basis, we establish and describe a structured reconstruction workflow. It spans background and noise preprocessing, precise calibration of the multifocal array, pixel-reassignment-based image reconstruction, and physics-informed deconvolution enhancement. Each module is examined in depth. Finally, together with an outlook on future MISM reconstruction algorithms, we expect this review to stimulate new reconstruction ideas and further support researchers in exploring the microscopic world in areas such as biochemistry and materials science.
Keywords:
computational microscopy
multifocal excitation
image scanning microscopy
super-resolution imaging
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