Automated Smartphone Based Cell Analysis Platform
| dc.contributor.author | Avci, M.B. | |
| dc.contributor.author | Kurul, F. | |
| dc.contributor.author | Turkan, M. | |
| dc.contributor.author | Çetin, A.E. | |
| dc.date.accessioned | 2025-12-30T15:59:38Z | |
| dc.date.available | 2025-12-30T15:59:38Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | Cell analysis technologies play a critical role in biomedical research, enabling precise evaluation of essential parameters such as cell viability, density, and confluency. In this article, we introduce Quantella, a smartphone-based platform designed to perform comprehensive cell analysis encompassing these key metrics. Addressing limitations of conventional systems, such as high cost, hardware complexity, and limited adaptability, Quantella integrates low-cost optics, a rinsable flow cell, bluetooth-enabled hardware control, and a cloud-connected mobile application. Its adaptive image-processing pipeline employs multi-exposure fusion, thresholding, and morphological filtering for accurate, morphology-independent segmentation without requiring deep learning or user-defined parameters. System validation studies across diverse cell types showed deviations under 5% from flow cytometry. With the capacity to analyze over 10,000 cells per test, Quantella delivers high-throughput, reproducible results. Its accessible, scalable design makes it a promising tool for biomedical research, diagnostics, and education, particularly in resource-limited settings. © The Author(s) 2025. | en_US |
| dc.identifier.doi | 10.1038/s44303-025-00093-z | |
| dc.identifier.issn | 2948-197X | |
| dc.identifier.scopus | 2-s2.0-105022241979 | |
| dc.identifier.uri | https://doi.org/10.1038/s44303-025-00093-z | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14365/8484 | |
| dc.language.iso | en | en_US |
| dc.publisher | Springer Nature | en_US |
| dc.relation.ispartof | NPJ Imaging | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.title | Automated Smartphone Based Cell Analysis Platform | en_US |
| dc.type | Article | en_US |
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| gdc.coar.access | open access | |
| gdc.coar.type | text::journal::journal article | |
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| gdc.description.department | İzmir Ekonomi Üniversitesi | en_US |
| gdc.description.departmenttemp | [Avci] Meryem Beyza, Izmir Biomedicine and Genome Center, Izmir, Izmir, Turkey, Department of Electrical and Electronic Engineering, Izmir Ekonomi Üniversitesi, Izmir, Turkey, Izmir International Biomedicine and Genome Institute, Dokuz Eylül Üniversitesi, Izmir, Turkey; [Kurul] Fatma, Izmir Biomedicine and Genome Center, Izmir, Izmir, Turkey; [Turkan] Mehmet, Department of Electrical and Electronic Engineering, Izmir Ekonomi Üniversitesi, Izmir, Turkey; [Çetin] Arif Engin, Izmir Biomedicine and Genome Center, Izmir, Izmir, Turkey, Department of Biophysics, Dokuz Eylül Üniversitesi, Izmir, Turkey | en_US |
| gdc.description.issue | 1 | en_US |
| gdc.description.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | N/A | |
| gdc.description.volume | 3 | en_US |
| gdc.description.wosquality | N/A | |
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| gdc.virtual.author | Türkan, Mehmet | |
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