ell counting is essential in life sciences, medicine, and pharmacology. Traditional approaches such as hemocytometry, require manual counting cells under a microscope. Although hemocytometry is cost-effective, it is also time-consuming and limited by operator experience. To address the drawbacks mentioned above, automated cell counting technologies have been developed to enhance the accuracy and efficiency of cell counting applications through the capture and processing of cell images. However, a limitation of these technologies is that they rely on counting a relatively small number of cells (100-200), indicating a need for further improvement. Additionally, these devices require specialized equipment such as counting chambers and solutions that are compatible with their hardware settings. In this study, we have developed an optofluidic cell-counting device that addresses these problems. Our optofluidic cell-counting platform significantly enhances test accuracy by scanning more than 2000 cells. The proposed method has error rate of <1% for cell viability and <5% for cell concentration results. Platform could provide the count results within only 1 minute, including sample loading, autofocusing, image recording and processing. Presented platform also has a built-in fluidic component that eliminates the need for an external counting chamber, enabling completely automated sample loading and self-cleaning capabilities compatible with any cleaning solutions. Providing a user-friendly and efficient functionality, our optofluidic platform has the potential to be a crucial resource for cost-effective and precise cell-counting applications
|