Optimization-based image reconstruction method for super-resolution structured-illumination microscopy

Bezzubik, V.V., Belashenkov, N.R., Vasiliev, V.N., Inochkin, F.M.

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For Russian citation (Opticheskii Zhurnal):

Беззубик В.В., Белашенков Н.Р., Васильев В.Н., Иночкин Ф.М. Оптимизационный метод реконструкции изображения для сверхразрешающей микроскопии структурированного освещения // Оптический журнал. 2019. Т. 86. № 12. С. 3–14. http://doi.org/10.17586/1023-5086-2019-86-12-03-14

Bezzubik V.V., Belashenkov N.R., Vasiliev V.N., Inochkin F.M. Optimization-based image reconstruction method for super-resolution structured-illumination microscopy [in Russian] // Opticheskii Zhurnal. 2019. V. 86. № 12. P. 3–14. http://doi.org/10.17586/1023-5086-2019-86-12-03-14

For citation (Journal of Optical Technology):

V. V. Bezzubik, N. R. Belashenkov, V. N. Vasilyev, and F. M. Inochkin, "Optimization-based image reconstruction method for super-resolution structured-illumination microscopy," Journal of Optical Technology. 86(12), 748-757 (2019). https://doi.org/10.1364/JOT.86.000748

Abstract:

This paper discuses the problem of reconstructing images in digital form with resolution that exceeds the limiting resolution of a diffraction-limited system from a set of images with spatially modulated illumination. The reconstruction method described here is based on a numerical–analytical solution of the problem of minimizing the mismatch functional of an array of recorded images with their mathematical model. Models of planar and three-dimensional objects are considered, and the effectiveness of the proposed method in computational experiments is demonstrated. By comparison with the classical reconstruction method, the proposed method is distinguished by good stability against deviations of the system parameters from the calculated values, allows the spatial-modulation parameters of the illumination to be automatically estimated, and makes it possible to use a priori knowledge concerning the signal to be reconstructed. Our results can be used when programs are being developed for reconstructing images in structured-illumination microscopy.

Keywords:

diffraction limit, optical super-resolution, structured-illumination microscopy, image reconstruction, deconvolution, optimization problem, conjugate-gradient method, iterative algorithm

Acknowledgements:

The research was carried out in ITMO University and was supported by the Ministry of Education and Science of the Russian Federation (project No. 074-11-2018-004).

OCIS codes: 100.3010, 100.664, 100.3190, 100.1830, 180.2520, 120.4120

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