2024/01/22 by Yuanyuan Wei, Wei, Yuanyuan, Shanhang Luo +19
Biochemistry, Genetics and Molecular Biology · Environmental Science · #Cell Image Analysis Techniques #FOS: Biological sciences #FOS: Electrical engineering #Gene expression and cancer classification #Health, Environment, Cognitive Aging #Image and Video Processing (eess.IV) #Quantitative Methods (q-bio.QM) #Systems and Control (eess.SY) #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2403.18826
openalex publication_date 2024/01/22 · openalex created_date 2024/03/30 · openalex updated_date 2026/07/28
Digital PCR (dPCR) has revolutionized nucleic acid diagnostics by enabling absolute quantification of rare mutations and target sequences. However, current detection methodologies face challenges, as flow cytometers are costly and complex, while fluorescence imaging methods, relying on software or manual counting, are time-consuming and prone to errors. To address these limitations, we present SAM-dPCR, a novel self-supervised learning-based pipeline that enables real-time and high-throughput absolute quantification of biological samples. Leveraging the zero-shot SAM model, SAM-dPCR efficiently analyzes diverse microreactors with over 97.7% accuracy within a rapid processing time of 3.16 seconds. By utilizing commonly available lab fluorescence microscopes, SAM-dPCR facilitates the quantification of sample concentrations. The accuracy of SAM-dPCR is validated by the strong linear relationship observed between known and inferred sample concentrations. Additionally, SAM-dPCR demonstrates versatility through comprehensive verification using various samples and reactor morphologies. This accessible, cost-effective tool transcends the limitations of traditional detection methods or fully supervised AI models, marking the first application of SAM in nucleic acid detection or molecular diagnostics. By eliminating the need for annotated training data, SAM-dPCR holds great application potential for nucleic acid quantification in resource-limited settings.