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

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.

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.

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.

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.

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.