DART让微流控芯片实时分析活细胞图像，5分钟定位全部区域。
DART: A design-aware microfluidic chip paradigm for real-time live-cell image analysis
- 通过嵌入标记点与深度学习，实现芯片设计图与实物对齐
- 每张图像处理耗时不足1.1秒，结构去除仅需40毫秒
- 适用于多种复杂芯片布局，适合高通量活细胞研究
高通量微流控活细胞成像产生大量单细胞数据。然而，传统半自动化流程需逐个定位感兴趣区域（RoI），并去除周围芯片结构，其耗时随区域数量增加而上升，导致分析延迟数小时至数天。本文提出设计感知且支持实时分析的DART范式，通过将CAD蓝图与物理芯片对齐，实现与通量无关的区域定位和跨多种几何形状与布局的全自动图像处理。DART利用嵌入式标识点和基于深度学习的检测算法完成对齐。在瑞士军刀芯片上验证：该芯片包含8种不同结构的区域，共1164个位置。DART可在5分钟内定位所有区域，40毫秒内清除原始图像中的微流控结构，并在每张图像1.1秒内完成包括细胞分割在内的全自动分析。这些能力使DART成为端到端软硬件协同的实时分析范式，为闭环、结果导向的智能显微镜铺平道路。
原文摘要 · Abstract (English)
High-throughput microfluidic live-cell imaging generates rich single-cell data. Yet semi-automated procedures for locating regions of interest (RoIs), each containing one cell population, and removing surrounding microfluidic structures from recorded images, scale with the number of RoIs. This prevents real-time image analysis and delays time-to-insight by hours to days. We introduce the Design-Aware and Real-Time capable (DART) paradigm for microfluidic cultivation chips, which aligns the CAD blueprint with the physical chip and thereby enables throughput-independent localization of all RoIs and fully automated image processing across diverse RoI geometries and chip layouts. DART establishes this alignment through embedded fiducial markers and deep-learning-based marker detection. We validate DART using the Swiss Army Knife chip, which combines eight structurally distinct RoI designs across 1164 RoI locations. DART localizes all RoIs in five minutes, removes microfluidic structures from raw microscopy images in 40 ms, and performs fully automated image analysis, including cell segmentation, in under 1.1 s per image. Together, these capabilities establish DART as an end-to-end hardware-software paradigm with real-time-capable analysis that paves the way toward closed-loop and outcome-driven smart microscopy.
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