Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy Data
Live-cell Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mrow><mn>2</mn><mo>+</mo></mrow></msup></semantics></math></in...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-10-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/22/21/11792 |
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| author | Lena-Marie Woelk Sukanya A. Kannabiran Valerie J. Brock Christine E. Gee Christian Lohr Andreas H. Guse Björn-Philipp Diercks René Werner |
| author_facet | Lena-Marie Woelk Sukanya A. Kannabiran Valerie J. Brock Christine E. Gee Christian Lohr Andreas H. Guse Björn-Philipp Diercks René Werner |
| author_sort | Lena-Marie Woelk |
| collection | DOAJ |
| description | Live-cell Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mrow><mn>2</mn><mo>+</mo></mrow></msup></semantics></math></inline-formula> fluorescence microscopy is a cornerstone of cellular signaling analysis and imaging. The demand for high spatial and temporal imaging resolution is, however, intrinsically linked to a low signal-to-noise ratio (SNR) of the acquired spatio-temporal image data, which impedes on the subsequent image analysis. Advanced deconvolution and image restoration algorithms can partly mitigate the corresponding problems but are usually defined only for <i>static</i> images. Frame-by-frame application to spatio-temporal image data neglects inter-frame contextual relationships and temporal consistency of the imaged biological processes. Here, we propose a variational approach to <i>time-dependent</i> image restoration built on entropy-based regularization specifically suited to process low- and lowest-SNR fluorescence microscopy data. The advantage of the presented approach is demonstrated by means of four datasets: synthetic data for in-depth evaluation of the algorithm behavior; two datasets acquired for analysis of initial Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mrow><mn>2</mn><mo>+</mo></mrow></msup></semantics></math></inline-formula> microdomains in T-cells; finally, to illustrate the transferability of the methodical concept to different applications, one dataset depicting spontaneous Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mrow><mn>2</mn><mo>+</mo></mrow></msup></semantics></math></inline-formula> signaling in jGCaMP7b-expressing astrocytes. To foster re-use and reproducibility, the source code is made publicly available. |
| first_indexed | 2024-03-10T06:01:08Z |
| format | Article |
| id | doaj.art-d866c1d7c1a5432ab339cbd65077aec0 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-10T06:01:08Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-d866c1d7c1a5432ab339cbd65077aec02023-11-22T20:57:58ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672021-10-0122211179210.3390/ijms222111792Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy DataLena-Marie Woelk0Sukanya A. Kannabiran 1Valerie J. Brock 2Christine E. Gee 3Christian Lohr 4Andreas H. Guse 5Björn-Philipp Diercks 6René Werner7Department of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, GermanyDepartment of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, GermanyDepartment of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, GermanyInstitute of Synaptic Physiology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, GermanyDivision of Neurophysiology, Institute of Zoology, University of Hamburg, 20146 Hamburg, GermanyDepartment of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, GermanyDepartment of Biochemistry and Molecular Cell Biology, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, GermanyDepartment of Computational Neuroscience, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, GermanyLive-cell Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mrow><mn>2</mn><mo>+</mo></mrow></msup></semantics></math></inline-formula> fluorescence microscopy is a cornerstone of cellular signaling analysis and imaging. The demand for high spatial and temporal imaging resolution is, however, intrinsically linked to a low signal-to-noise ratio (SNR) of the acquired spatio-temporal image data, which impedes on the subsequent image analysis. Advanced deconvolution and image restoration algorithms can partly mitigate the corresponding problems but are usually defined only for <i>static</i> images. Frame-by-frame application to spatio-temporal image data neglects inter-frame contextual relationships and temporal consistency of the imaged biological processes. Here, we propose a variational approach to <i>time-dependent</i> image restoration built on entropy-based regularization specifically suited to process low- and lowest-SNR fluorescence microscopy data. The advantage of the presented approach is demonstrated by means of four datasets: synthetic data for in-depth evaluation of the algorithm behavior; two datasets acquired for analysis of initial Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mrow><mn>2</mn><mo>+</mo></mrow></msup></semantics></math></inline-formula> microdomains in T-cells; finally, to illustrate the transferability of the methodical concept to different applications, one dataset depicting spontaneous Ca<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mrow></mrow><mrow><mn>2</mn><mo>+</mo></mrow></msup></semantics></math></inline-formula> signaling in jGCaMP7b-expressing astrocytes. To foster re-use and reproducibility, the source code is made publicly available.https://www.mdpi.com/1422-0067/22/21/11792Ca<sup>2+</sup> imagingfluorescence microscopylive-cell imaginglow signal-to-noise ratiodeconvolutionimage restoration |
| spellingShingle | Lena-Marie Woelk Sukanya A. Kannabiran Valerie J. Brock Christine E. Gee Christian Lohr Andreas H. Guse Björn-Philipp Diercks René Werner Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy Data International Journal of Molecular Sciences Ca<sup>2+</sup> imaging fluorescence microscopy live-cell imaging low signal-to-noise ratio deconvolution image restoration |
| title | Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy Data |
| title_full | Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy Data |
| title_fullStr | Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy Data |
| title_full_unstemmed | Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy Data |
| title_short | Time-Dependent Image Restoration of Low-SNR Live-Cell Ca<sup>2</sup> Fluorescence Microscopy Data |
| title_sort | time dependent image restoration of low snr live cell ca sup 2 sup fluorescence microscopy data |
| topic | Ca<sup>2+</sup> imaging fluorescence microscopy live-cell imaging low signal-to-noise ratio deconvolution image restoration |
| url | https://www.mdpi.com/1422-0067/22/21/11792 |
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