IEEE Trans Nanobioscience. 2019 Jul;18(3):373-380. doi: 10.1109/TNB.2019.2904009. Epub 2019 Mar 8.
This paper reports a vision-based automated microfluidic system for morphological measurement and size-based sorting of the nematode worm C. elegans. Exceeding the capabilities of conventional worm sorting microfluidic devices purely relying on passive sorting mechanisms, our system is capable of accurate measurement of the worm length/width and active sorting of worms with the desired sizes from a mixture of worms with different body sizes. This function is realized based on the combination of real-time, vision-based worm detection and sizing algorithms and automated on-chip worm manipulation. A double-layer microfluidic device with computer-controlled pneumatic valves is developed for sequential loading, trapping, vision-based sizing, and sorting of single worms. To keep the system operation robust, vision-based algorithms on detecting multi-worm loading and worm sizing failure have also been developed. We conducted sorting experiments on 319 worms and achieved an average sorting speed of 10.4 worms per minute (5.8 s/worm) with an operation success rate of 90.3%. This system will facilitate the worm biology studies where body size measurement and size-based sorting of many worms are needed.
本文报道了一种基于视觉的自动化微流控系统，用于秀丽隐杆线虫的形态测量和基于大小的分选。与纯粹依赖于被动分选机制的传统线虫分选微流控设备相比，我们的系统能够精确测量线虫的长度/宽度，并从具有不同身体大小的线虫混合物中主动分选所需大小的线虫。该功能基于实时、基于视觉的线虫检测和尺寸算法以及自动的芯片上线虫操作的组合来实现。开发了一种具有计算机控制气动阀的双层微流控装置，用于顺序加载、捕获、基于视觉的单个线虫尺寸测量和分选。为了保持系统运行的稳健性，还开发了基于视觉的多线虫加载和线虫尺寸测量失败检测算法。我们对 319 条线虫进行了分选实验，平均分选速度为 10.4 条/分钟（5.8 秒/条），操作成功率为 90.3%。该系统将有助于需要进行大量线虫的身体尺寸测量和基于尺寸分选的线虫生物学研究。
