Abstract
The development of a digital polymerase chain reaction (dPCR) system typically begins with an idea for the system configuration and chip layout, followed by design, fabrication, and hardware testing. The image processing software can be developed and verified based on the test results.
In this paper, we proposed a dPCR emulation methodology to train the developed image processing software before building the dPCR system hardware. We developed a script in a MATLAB environment to generate artificial dPCR images and emulate the dPCR results.
First, we defined the number of parameters corresponding to the emulated results, such as the number of partitions with targets, background fluorescence distribution and intensity, image defects, image rotation angle, shift, non-uniform light distribution, and temperature sensitivity. We then implemented the defined parameters and generated an artificial dPCR chip image based on layout design or pattern recognition algorithm.
Finally, we obtained a dataset from the artificial image for subsequent result analysis. The generated images could then be used to train the image processing algorithms based on the requirements.
We verified the proposed method using various designs of dPCR chips from recently published papers, demonstrating the method's versatility. The proposed method also demonstrated the capability for separating the software and hardware development.
Thus, our method allowed the image processing and hardware to be concurrently designed and tested simplifying and speeding up the dPCR system development.