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https://dspace.iiti.ac.in/handle/123456789/18632
| Title: | IRIS: Automated mobile microscope instrument for white blood cell classification |
| Authors: | Kumar, Rajesh Dixit, Aditya Srivastava, Adit Gupta, Puneet |
| Issue Date: | 2026 |
| Publisher: | Elsevier B.V. |
| Citation: | Kumar, R., Bagla, A., Dixit, A., Srivastava, A., Gupta, P., Gupta, V., & Kharbanda, J. (2026). IRIS: Automated mobile microscope instrument for white blood cell classification. Measurement: Journal of the International Measurement Confederation, 283. https://doi.org/10.1016/j.measurement.2026.122096 |
| Abstract: | White blood cell (WBC) classification is vital for early disease diagnosis. Traditional WBC classification relies on bulky, expensive microscopes and skilled pathologists for manual analysis. However, this approach is prone to bias and requires substantial expertise. Mobile microscope (MM) has emerged as a promising alternative by integrating smartphone cameras with a portable microscope instrument. Existing MMs often suffer from insufficient magnification, require manual slide movement, or use costly components, making them difficult for WBC classification. To address these limitations, we introduce IRIS: automated mobIle micRoscope instrument for whIte blood cell claSsification, a cost-effective, user-friendly MM instrument that seamlessly integrates with smartphones. IRIS can scan the entire slide at high resolution using a 45× objective lens integrated with a 15× eyepiece, providing significantly improved magnification for capturing high-quality images suitable for WBC classification. It also incorporates an automated slide movement system with X–Y traversal, eliminating manual adjustments. The device weighs approximately 1 kg and is housed in a compact 130 × 100 × 150 cubic millimetres enclosure, ensuring portability. Instrument measurements were performed using a USAF 1951 resolution test chart and a stage micrometer. To compare the resolution measurement, the same USAF 1951 resolution test chart and stage micrometer were imaged with a conventional microscope, and the results were comparable. Both qualitative and quantitative evaluations demonstrate that the acquired WBC images closely resemble those from publicly available datasets and are well-suited for WBC classification. These results show the feasibility of IRIS as a portable MM instrument for WBC classification. © 2026 Elsevier Ltd |
| URI: | https://dx.doi.org/10.1016/j.measurement.2026.122096 https://dspace.iiti.ac.in:8080/jspui/handle/123456789/18632 |
| ISSN: | 0263-2241 |
| Type of Material: | Journal Article |
| Appears in Collections: | Department of Computer Science and Engineering |
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