Evaluation of Fluorescence Detection Algorithms for Efficient ROI Setting in Low-Cost Real-Time PCR Systems

This study proposes a region of interest (ROI) setting method to improve the accuracy and efficiency of fluorescence detection in a compact real-time multiplex fluorescence PCR system. Conventional commercial real-time PCR systems are limited in point-of-care (POC) environments due to their high cost and complex optical structures. To address this issue, we developed a low-cost, compact system using an open-platform camera and a Fresnel lens. However, in such a simply structured system, variations between the wells of the polymerase chain reaction (PCR) plate may affect the accuracy of fluorescence detection. In this study, after capturing images with a CMOS camera, we propose two ROI image processing algorithms. The proposed algorithms reliably extract fluorescence signals and compare ROI deviations caused by variations between wells to determine whether physical correction is necessary. To validate the system, we performed comparative analysis of real-time DNA amplification images and fluorescence dye images collected over multiple periods. Based on evaluations using manual detection as a reference, it was confirmed that even a simple algorithm can achieve stable fluorescence detection while minimizing ROI distortion. This study presents an efficient method for enhancing the accuracy of quantitative fluorescence analysis in small PCR systems and is expected to contribute to improving the performance of point-of-care diagnostics, thereby increasing accessibility to on-site diagnostics in the future.

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Publication Details

Journal
Biosensors
Published
2025-09-10
DOI
https://doi.org/10.3390/bios15090598
Primary Topic
Biosensors and Analytical Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Evaluation of Fluorescence Detection Algorithms for Efficient ROI Setting in Low-Cost Real-Time PCR Systems

Chan-Young Park, Ji-Soo Hwang, Deuk-Ju Lee, Seul-Bit-Na Koo
Biosensors
Biosensors and Analytical Detection
article

Evaluation of Fluorescence Detection Algorithms for Efficient ROI Setting in Low-Cost Real-Time PCR Systems

Chan-Young Park, Ji-Soo Hwang, Deuk-Ju Lee, Seul-Bit-Na Koo
article en

Abstract

This study proposes a region of interest (ROI) setting method to improve the accuracy and efficiency of fluorescence detection in a compact real-time multiplex fluorescence PCR system. Conventional commercial real-time PCR systems are limited in point-of-care (POC) environments due to their high cost and complex optical structures. To address this issue, we developed a low-cost, compact system using an open-platform camera and a Fresnel lens. However, in such a simply structured system, variations between the wells of the polymerase chain reaction (PCR) plate may affect the accuracy of fluorescence detection. In this study, after capturing images with a CMOS camera, we propose two ROI image processing algorithms. The proposed algorithms reliably extract fluorescence signals and compare ROI deviations caused by variations between wells to determine whether physical correction is necessary. To validate the system, we performed comparative analysis of real-time DNA amplification images and fluorescence dye images collected over multiple periods. Based on evaluations using manual detection as a reference, it was confirmed that even a simple algorithm can achieve stable fluorescence detection while minimizing ROI distortion. This study presents an efficient method for enhancing the accuracy of quantitative fluorescence analysis in small PCR systems and is expected to contribute to improving the performance of point-of-care diagnostics, thereby increasing accessibility to on-site diagnostics in the future.

BiosensorsVol. 15(9)
Hallym University (KR)
Hallym University
Openalex Percentile: Top 77%
Biosensors and Analytical Detection
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Evaluation of Fluorescence Detection Algorithms for Efficient ROI Setting in Low-Cost Real-Time PCR Systems — Chan-Young Park, Ji-Soo Hwang, et al. · Biosensors (2025) | TGRS Research Map | TGRS