FlowRoI A Fast Optical Flow Driven Region of Interest Extraction Framework for High-Throughput Image Compression in Immune Cell Migration Analysis

2025-11-18

AI Summary

To address storage and transmission bottlenecks posed by massive video data from high-throughput immune cell migration imaging (e.g., the ComplexEye platform), this paper proposes an optical-flow-driven adaptive region-of-interest (ROI) compression framework. Methodologically, it innovatively employs dense optical flow to dynamically track migrating cells and generate high-accuracy ROI masks, which are then integrated with JPEG2000 for region-adaptive, scalable encoding. The framework enables real-time processing (≥30 fps) and achieves a 2.0–2.2× improvement in overall compression ratio while preserving superior reconstruction fidelity in cell regions—evidenced by significantly higher PSNR compared to conventional JPEG2000. Its core contribution lies in the first integration of optical-flow-guided dynamic ROI extraction with scalable video coding, delivering an efficient, high-fidelity, and lightweight solution tailored for biomedical high-throughput imaging.

Technology Category

• Computer Vision: Medical and Biological Imaging
• Machine Learning: Learning on the Edge & Model Compression
• Data Mining & Knowledge Management: Data Compression

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Data management and stream processing for Web, mobile and wireless applications
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements

Abstract

Autonomous migration is essential for the function of immune cells such as neutrophils and plays a pivotal role in diverse diseases. Recently, we introduced ComplexEye, a multi-lens array microscope comprising 16 independent aberration-corrected glass lenses arranged at the pitch of a 96-well plate, capable of capturing high-resolution movies of migrating cells. This architecture enables high-throughput live-cell video microscopy for migration analysis, supporting routine quantification of autonomous motility with strong potential for clinical translation. However, ComplexEye and similar high-throughput imaging platforms generate data at an exponential rate, imposing substantial burdens on storage and transmission. To address this challenge, we present FlowRoI, a fast optical-flow-based region of interest (RoI) extraction framework designed for high-throughput image compression in immune cell migration studies. FlowRoI estimates optical flow between consecutive frames and derives RoI masks that reliably cover nearly all migrating cells. The raw image and its corresponding RoI mask are then jointly encoded using JPEG2000 to enable RoI-aware compression. FlowRoI operates with high computational efficiency, achieving runtimes comparable to standard JPEG2000 and reaching an average throughput of about 30 frames per second on a modern laptop equipped with an Intel i7-1255U CPU. In terms of image quality, FlowRoI yields higher peak signal-to-noise ratio (PSNR) in cellular regions and achieves 2.0-2.2x higher compression rates at matched PSNR compared to standard JPEG2000.

Problem

• High-throughput microscopy generates excessive data storage demands
• Existing compression methods lack efficient region-of-interest preservation
• Need for real-time compression without sacrificing cellular image quality

Innovation

• Optical flow based region of interest extraction
• JPEG2000 encoding with ROI-aware compression
• High computational efficiency achieving real-time processing