A new dynamic deep learning noise elimination method for chip-based real-time PCR.

ABSTRACT: Point-of-care (POC) real-time polymerase chain reaction (PCR) has become one of the most important technologies for many fields such as pathogen detection and water-quality monitoring. POC real-time PCR usually adopts chips with small-volume chambers for portability, which is more likely to produce complex noise that seriously affects the accuracy. Such complex noises are difficult to be eliminated by the traditional fixed area algorithm that is most commonly used at present because they usually have random shape, location, and brightness. To address this problem, we proposed a novel image analysis method, Dynamic Deep Learning Noise Elimination Method (DIPLOID), in this paper. Our new method could recognize and output the mask of the interference by Mask R-CNN, and then subtract the inter

SUBMITTER: Zhang B 

PROVIDER: S-EPMC8976108 | biostudies-literature | 2022 May

REPOSITORIES: biostudies-literature