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

Area of Science:

• Biomedical Optics
• Computational Imaging
• Cell Biology

Background:

• Quantitative Phase Microscopy (QPM) is crucial for cell morphology studies.
• High-throughput QPM is needed for clinical applications, requiring faster data processing.
• Current QPM methods face challenges in processing large datasets efficiently.

Purpose of the Study:

• To develop a high-throughput data processing pipeline for Quantitative Phase Microscopy (QPM).
• To leverage a system-on-module approach for real-time QPM data processing.
• To accelerate the analysis of cell populations using holographic cytometry (HC).

Main Methods:

• Developed a real-time processing pipeline using NVIDIA Jetson Orin Nano for parallel processing.
• Implemented a CUDA algorithm for QPM data generation, phase unwrapping, cell segmentation, and refocusing.
• Demonstrated the pipeline on a holographic cytometry (HC) system for high-throughput QPM.

Main Results:

• Processed over 107,000 red blood cell images.
• Achieved a processing speed of 1200 cells/second.
• Real-time refocusing demonstrated high structural similarity to traditional methods.

Conclusions:

• The developed pipeline accelerates statistical analysis of cell populations.
• This advancement supports the development of portable, low-cost holographic cytometry systems.
• The study paves the way for more efficient clinical applications of QPM.