Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices
Fluorescence microscopy enabled by smartphone-coupled 3D instruments has shown utility in different biomedical applications ranging from diagnostics to biomanufacturing. Recently, we have designed and developed these devices and have demonstrated their utility in micro-nano particle sensing and leuk...
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MDPI AG
2025-06-01
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| Series: | Biosensors |
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| Online Access: | https://www.mdpi.com/2079-6374/15/7/403 |
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| author | Muhammad Ahsan Sami Muhammad Nabeel Tahir Umer Hassan |
| author_facet | Muhammad Ahsan Sami Muhammad Nabeel Tahir Umer Hassan |
| author_sort | Muhammad Ahsan Sami |
| collection | DOAJ |
| description | Fluorescence microscopy enabled by smartphone-coupled 3D instruments has shown utility in different biomedical applications ranging from diagnostics to biomanufacturing. Recently, we have designed and developed these devices and have demonstrated their utility in micro-nano particle sensing and leukocyte imaging. Here, we present a novel application for enhancing the imaging performance of smartphone fluorescence microscopes (SFM) and reducing their operational complexity. Computational noise correction is employed using 3D Averaging and 3D Gaussian filters of different kernel sizes (3 × 3 × 3, 7 × 7 × 7, 11 × 11 × 11, 15 × 15 × 15, and 21 × 21 × 21) and various standard deviations σ (for Gaussian only). Fluorescent beads of different sizes (8.3, 2, 1, 0.8 µm) were imaged using a custom-designed SFM. The application of the computational filters significantly enhanced the signal quality of particle detection in the captured fluorescent images. Amongst the Averaging filters, a kernel size of 21 × 21 × 21 produced the best results for all bead sizes, and similarly, amongst Gaussian filters, σ equal to 5 and a kernel size equal to 21 × 21 × 21 produced the best results. This visual improvement was then quantified by calculating the signal-difference-to-noise ratio (SDNR) and contrast-to-noise ratio (CNR) of filtered and unfiltered original images using a custom-developed quality assessment algorithm (AQAFI). Lastly, noise correction using Averaging and Gaussian filters with the previously identified optimal parameters was applied to images of fluorescently tagged human peripheral blood leukocytes captured using an SFM under various conditions. The ubiquitous nature and simplistic application of these filters enable their utility with a range of existing fluorescence microscope designs, thus allowing us to enhance their imaging capabilities. |
| format | Article |
| id | doaj-art-d884e739b3654ba3ad1d3a96b0965d73 |
| institution | Kabale University |
| issn | 2079-6374 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
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| series | Biosensors |
| spelling | doaj-art-d884e739b3654ba3ad1d3a96b0965d732025-08-20T03:58:31ZengMDPI AGBiosensors2079-63742025-06-0115740310.3390/bios15070403Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy DevicesMuhammad Ahsan Sami0Muhammad Nabeel Tahir1Umer Hassan2Department of Electrical and Computer Engineering, School of Engineering, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USADepartment of Electrical and Computer Engineering, School of Engineering, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USADepartment of Electrical and Computer Engineering, School of Engineering, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901, USAFluorescence microscopy enabled by smartphone-coupled 3D instruments has shown utility in different biomedical applications ranging from diagnostics to biomanufacturing. Recently, we have designed and developed these devices and have demonstrated their utility in micro-nano particle sensing and leukocyte imaging. Here, we present a novel application for enhancing the imaging performance of smartphone fluorescence microscopes (SFM) and reducing their operational complexity. Computational noise correction is employed using 3D Averaging and 3D Gaussian filters of different kernel sizes (3 × 3 × 3, 7 × 7 × 7, 11 × 11 × 11, 15 × 15 × 15, and 21 × 21 × 21) and various standard deviations σ (for Gaussian only). Fluorescent beads of different sizes (8.3, 2, 1, 0.8 µm) were imaged using a custom-designed SFM. The application of the computational filters significantly enhanced the signal quality of particle detection in the captured fluorescent images. Amongst the Averaging filters, a kernel size of 21 × 21 × 21 produced the best results for all bead sizes, and similarly, amongst Gaussian filters, σ equal to 5 and a kernel size equal to 21 × 21 × 21 produced the best results. This visual improvement was then quantified by calculating the signal-difference-to-noise ratio (SDNR) and contrast-to-noise ratio (CNR) of filtered and unfiltered original images using a custom-developed quality assessment algorithm (AQAFI). Lastly, noise correction using Averaging and Gaussian filters with the previously identified optimal parameters was applied to images of fluorescently tagged human peripheral blood leukocytes captured using an SFM under various conditions. The ubiquitous nature and simplistic application of these filters enable their utility with a range of existing fluorescence microscope designs, thus allowing us to enhance their imaging capabilities.https://www.mdpi.com/2079-6374/15/7/403smartphone fluorescence microscope (SFM)micro/nanoparticlesleukocytesimage quality enhancementimaging filters |
| spellingShingle | Muhammad Ahsan Sami Muhammad Nabeel Tahir Umer Hassan Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices Biosensors smartphone fluorescence microscope (SFM) micro/nanoparticles leukocytes image quality enhancement imaging filters |
| title | Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices |
| title_full | Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices |
| title_fullStr | Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices |
| title_full_unstemmed | Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices |
| title_short | Enhancing Biomarker Detection and Imaging Performance of Smartphone Fluorescence Microscopy Devices |
| title_sort | enhancing biomarker detection and imaging performance of smartphone fluorescence microscopy devices |
| topic | smartphone fluorescence microscope (SFM) micro/nanoparticles leukocytes image quality enhancement imaging filters |
| url | https://www.mdpi.com/2079-6374/15/7/403 |
| work_keys_str_mv | AT muhammadahsansami enhancingbiomarkerdetectionandimagingperformanceofsmartphonefluorescencemicroscopydevices AT muhammadnabeeltahir enhancingbiomarkerdetectionandimagingperformanceofsmartphonefluorescencemicroscopydevices AT umerhassan enhancingbiomarkerdetectionandimagingperformanceofsmartphonefluorescencemicroscopydevices |