Real-time processing of high-throughput quantitative phase microscopy data using a Jetson Orin Nano.

Significance: Quantitative phase microscopy (QPM) is a holographic imaging technique often applied to studying cell morphology. To advance QPM for clinical applications, high-throughput implementations have been developed to allow imaging of thousands of cells at a time. Aim: To meet the needs of processing raw data and creating QPM holographic images, higher throughput processing methods are needed. Here, we report on the use of a system-on-module approach for QPM data processing. Approach: We have developed a real-time processing pipeline that leverages the parallel processing capabilities of the NVIDIA Jetson Orin Nano to implement processing of cell data. We demonstrate this pipeline on a holographic cytometry (HC) system, a high-throughput QPM implementation. The CUDA processing algorithm enables the generation of QPM data from raw interferograms followed by phase unwrapping, cell segmentation, and refocusing. Result: We captured, processed, and analyzed 107,631 red blood cell images. The processing speed reaches 1200 cells/s in the speed test. Benchmarking shows that real-time refocusing maintains a high degree of structural similarity to the traditional refocusing method. Conclusion: The result demonstrates that our pipeline could accelerate the statistical analysis of cell populations. We expect this study to benefit the development of a portable, low-cost HC system.