A novel fluorescence microscopy image deconvolution approach

Jing Qin; Xiyu Yi; Shimon Weiss

doi:10.1109/ISBI.2018.8363611

A novel fluorescence microscopy image deconvolution approach

Jing Qin, Xiyu Yi, Shimon Weiss

Mathematics

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

Superresolution optical fluctuation imaging (SOFI) is an attractive and affordable alternative to more established superresolution imaging methods. It provides moderate resolution enhancement and an efficient estimation of the optical point spread function (PSF). Moreover, further resolution enhancement could be achieved by deconvolution of the SOFI image. In this paper, we propose a novel image deconvolution approach based on the shearlet transform and the fractional-order total variation (FOTV) to further improve SOFI images. Since SOFI PSF estimation is imperfect in practice, we also propose a prior-guided semi-blind deconvolution method. Numerical experiments on simulated images with microtubule-like structures have shown that our proposed algorithms can recover filamentous features with high accuracy and outperforms other state-of-the-art deconvolution methods.

Original language	English
Title of host publication	2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018
Pages	441-444
Number of pages	4
ISBN (Electronic)	9781538636367
DOIs	https://doi.org/10.1109/ISBI.2018.8363611
State	Published - May 23 2018
Event	15th IEEE International Symposium on Biomedical Imaging, ISBI 2018 - Washington, United States Duration: Apr 4 2018 → Apr 7 2018

Publication series

Name	Proceedings - International Symposium on Biomedical Imaging
Volume	2018-April
ISSN (Print)	1945-7928
ISSN (Electronic)	1945-8452

Conference

Conference	15th IEEE International Symposium on Biomedical Imaging, ISBI 2018
Country/Territory	United States
City	Washington
Period	4/4/18 → 4/7/18

Bibliographical note

Funding Information:
The work from S. Weiss and X. Yi was supported by Dean Willard Chair fund and STROBE: A National Science Foundation Science & Technology Center under Grant No. DMR 1548924.

Publisher Copyright:
© 2018 IEEE.

Keywords

Alternating direction method of multipliers
Alternating minimization algorithm
Fractional-order total variation
Image deconvolution
SOFI
Shearlet transform

ASJC Scopus subject areas

Biomedical Engineering
Radiology Nuclear Medicine and imaging

Access to Document

10.1109/ISBI.2018.8363611

Cite this

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title = "A novel fluorescence microscopy image deconvolution approach",

abstract = "Superresolution optical fluctuation imaging (SOFI) is an attractive and affordable alternative to more established superresolution imaging methods. It provides moderate resolution enhancement and an efficient estimation of the optical point spread function (PSF). Moreover, further resolution enhancement could be achieved by deconvolution of the SOFI image. In this paper, we propose a novel image deconvolution approach based on the shearlet transform and the fractional-order total variation (FOTV) to further improve SOFI images. Since SOFI PSF estimation is imperfect in practice, we also propose a prior-guided semi-blind deconvolution method. Numerical experiments on simulated images with microtubule-like structures have shown that our proposed algorithms can recover filamentous features with high accuracy and outperforms other state-of-the-art deconvolution methods.",

keywords = "Alternating direction method of multipliers, Alternating minimization algorithm, Fractional-order total variation, Image deconvolution, SOFI, Shearlet transform",

author = "Jing Qin and Xiyu Yi and Shimon Weiss",

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doi = "10.1109/ISBI.2018.8363611",

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Qin, J, Yi, X & Weiss, S 2018, A novel fluorescence microscopy image deconvolution approach. in 2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. Proceedings - International Symposium on Biomedical Imaging, vol. 2018-April, pp. 441-444, 15th IEEE International Symposium on Biomedical Imaging, ISBI 2018, Washington, United States, 4/4/18. https://doi.org/10.1109/ISBI.2018.8363611

A novel fluorescence microscopy image deconvolution approach. / Qin, Jing; Yi, Xiyu; Weiss, Shimon.
2018 IEEE 15th International Symposium on Biomedical Imaging, ISBI 2018. 2018. p. 441-444 (Proceedings - International Symposium on Biomedical Imaging; Vol. 2018-April).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Weiss, Shimon

N1 - Funding Information: The work from S. Weiss and X. Yi was supported by Dean Willard Chair fund and STROBE: A National Science Foundation Science & Technology Center under Grant No. DMR 1548924. Publisher Copyright: © 2018 IEEE.

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Y1 - 2018/5/23

N2 - Superresolution optical fluctuation imaging (SOFI) is an attractive and affordable alternative to more established superresolution imaging methods. It provides moderate resolution enhancement and an efficient estimation of the optical point spread function (PSF). Moreover, further resolution enhancement could be achieved by deconvolution of the SOFI image. In this paper, we propose a novel image deconvolution approach based on the shearlet transform and the fractional-order total variation (FOTV) to further improve SOFI images. Since SOFI PSF estimation is imperfect in practice, we also propose a prior-guided semi-blind deconvolution method. Numerical experiments on simulated images with microtubule-like structures have shown that our proposed algorithms can recover filamentous features with high accuracy and outperforms other state-of-the-art deconvolution methods.

AB - Superresolution optical fluctuation imaging (SOFI) is an attractive and affordable alternative to more established superresolution imaging methods. It provides moderate resolution enhancement and an efficient estimation of the optical point spread function (PSF). Moreover, further resolution enhancement could be achieved by deconvolution of the SOFI image. In this paper, we propose a novel image deconvolution approach based on the shearlet transform and the fractional-order total variation (FOTV) to further improve SOFI images. Since SOFI PSF estimation is imperfect in practice, we also propose a prior-guided semi-blind deconvolution method. Numerical experiments on simulated images with microtubule-like structures have shown that our proposed algorithms can recover filamentous features with high accuracy and outperforms other state-of-the-art deconvolution methods.

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A novel fluorescence microscopy image deconvolution approach

Abstract

Publication series

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Bibliographical note

Keywords

ASJC Scopus subject areas

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