DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects
Abstract Background Quantitative phase imaging (QPI) is an established tool for the marker-free classification and quantitative characterization of biological samples. For spherical objects, such as cells in suspension, microgel beads, or liquid droplets, a single QPI image is sufficient to extract...
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| Format: | Article |
| Language: | English |
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BMC
2020-06-01
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| Series: | BMC Bioinformatics |
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| Online Access: | http://link.springer.com/article/10.1186/s12859-020-03553-y |
| _version_ | 1818061230476099584 |
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| author | Paul Müller Gheorghe Cojoc Jochen Guck |
| author_facet | Paul Müller Gheorghe Cojoc Jochen Guck |
| author_sort | Paul Müller |
| collection | DOAJ |
| description | Abstract Background Quantitative phase imaging (QPI) is an established tool for the marker-free classification and quantitative characterization of biological samples. For spherical objects, such as cells in suspension, microgel beads, or liquid droplets, a single QPI image is sufficient to extract the radius and the average refractive index. This technique is invaluable, as it allows the characterization of large sample populations at high measurement rates. However, until now, no universal software existed that could perform this type of analysis. Besides the choice of imaging modality and the variety in imaging software, the main difficulty has been to automate the entire analysis pipeline from raw data to ensemble statistics. Results We present DryMass, a powerful tool for QPI that covers all relevant steps from loading experimental data (multiple file formats supported), computing the phase data (built-in, automated hologram analysis), performing phase background corrections (offset, tilt, second order polynomial) to fitting scattering models (light projection, Rytov approximation, Mie simulations) to spherical phase objects for the extraction of dry mass, radius, and average refractive index. The major contribution of DryMass is a user-convenient, reliable, reproducible, and automated analysis pipeline for an arbitrary number of QPI datasets of arbitrary sizes. Conclusion DryMass is a leap forward for data analysis in QPI, as it not only makes it easier to visualize raw QPI data and reproduce previous results in the field, but it also opens up QPI analysis to users without a background in programming or phase imaging. |
| first_indexed | 2024-12-10T13:45:01Z |
| format | Article |
| id | doaj.art-69cbb6a0fed44414a11d96f08e885f64 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-10T13:45:01Z |
| publishDate | 2020-06-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-69cbb6a0fed44414a11d96f08e885f642022-12-22T01:46:28ZengBMCBMC Bioinformatics1471-21052020-06-012111810.1186/s12859-020-03553-yDryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objectsPaul Müller0Gheorghe Cojoc1Jochen Guck2Biotechnology Center, Center for Molecular and Cellular Bioengineering, Technische Universität DresdenBiotechnology Center, Center for Molecular and Cellular Bioengineering, Technische Universität DresdenBiotechnology Center, Center for Molecular and Cellular Bioengineering, Technische Universität DresdenAbstract Background Quantitative phase imaging (QPI) is an established tool for the marker-free classification and quantitative characterization of biological samples. For spherical objects, such as cells in suspension, microgel beads, or liquid droplets, a single QPI image is sufficient to extract the radius and the average refractive index. This technique is invaluable, as it allows the characterization of large sample populations at high measurement rates. However, until now, no universal software existed that could perform this type of analysis. Besides the choice of imaging modality and the variety in imaging software, the main difficulty has been to automate the entire analysis pipeline from raw data to ensemble statistics. Results We present DryMass, a powerful tool for QPI that covers all relevant steps from loading experimental data (multiple file formats supported), computing the phase data (built-in, automated hologram analysis), performing phase background corrections (offset, tilt, second order polynomial) to fitting scattering models (light projection, Rytov approximation, Mie simulations) to spherical phase objects for the extraction of dry mass, radius, and average refractive index. The major contribution of DryMass is a user-convenient, reliable, reproducible, and automated analysis pipeline for an arbitrary number of QPI datasets of arbitrary sizes. Conclusion DryMass is a leap forward for data analysis in QPI, as it not only makes it easier to visualize raw QPI data and reproduce previous results in the field, but it also opens up QPI analysis to users without a background in programming or phase imaging.http://link.springer.com/article/10.1186/s12859-020-03553-yDigital holographyQuantitative phase imagingRefractive indexCell analysisCell characterizationRytov approximation |
| spellingShingle | Paul Müller Gheorghe Cojoc Jochen Guck DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects BMC Bioinformatics Digital holography Quantitative phase imaging Refractive index Cell analysis Cell characterization Rytov approximation |
| title | DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects |
| title_full | DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects |
| title_fullStr | DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects |
| title_full_unstemmed | DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects |
| title_short | DryMass: handling and analyzing quantitative phase microscopy images of spherical, cell-sized objects |
| title_sort | drymass handling and analyzing quantitative phase microscopy images of spherical cell sized objects |
| topic | Digital holography Quantitative phase imaging Refractive index Cell analysis Cell characterization Rytov approximation |
| url | http://link.springer.com/article/10.1186/s12859-020-03553-y |
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