[1]李浩亮,乔琳博,李佳凝,等.基于 YOLOv11 和类血管芯片的循环肿瘤细胞检测[J].郑州大学学报(工学版),2027,48(XX):1-8.[doi:10.13705/j.issn.1671-6833.2026.04.005]
　LI Haoliang,QIAO Linbo,LI Jianing,et al.Circulating Tumour Cell Detection Based on YOLOv11 and Vascular-like Chip[J].Journal of Zhengzhou University (Engineering Science),2027,48(XX):1-8.[doi:10.13705/j.issn.1671-6833.2026.04.005]
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基于 YOLOv11 和类血管芯片的循环肿瘤细胞检测()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
48
期数:
2027年XX
页码:
1-8
栏目:
出版日期:
2027-12-10

文章信息/Info

Title:
Circulating Tumour Cell Detection Based on YOLOv11 and Vascular-like Chip
作者:
李浩亮; 乔琳博; 李佳凝; 杨潇楠
郑州大学 电气与信息工程学院，河南 郑州 450001
Author(s):
LI Haoliang;  QIAO Linbo;  LI Jianing;  YANG Xiaonan
School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China
关键词:
微流控;  血液循环;  类血管芯片;  循环肿瘤细胞;  YOLOv11
Keywords:
microfluidics;  blood circulation;  vessel-like chip;  circulating tumor cells;  YOLOv11
分类号:
TH789 TP391.4 R318.6
DOI:
10.13705/j.issn.1671-6833.2026.04.005
文献标志码:
A
摘要:
针对因血液中大量正常细胞的干扰，在全血样本中难以准确识别低丰度的循环肿瘤细胞（CTC）的问题，基于微流控技术，提出一套微流控类血管芯片与蠕动泵的动态血液循环平台，结合明场高速成像与YOLOv11目标检测，实现对全血中的CTC的无标记检测。系统通过使用蠕动泵模拟血液流动，构建了具有血液循环特性的流动环境，芯片采用多级分叉与40 μm微筛结构，依照细胞与血管尺寸优化通道尺寸；构建了包含CTC（人结肠癌细胞HT29模型）、RBC、WBC、PLT这4类细胞的图像数据集，实验结果表明，该系统对CTC检测mAP为98.65%，检测精确度以及召回率均大于99%，并展示了连续帧的在线检测。所提系统能够模拟体外血液循环并且在全血样本中准确识别CTC，具有较高的准确性与稳定性，为肿瘤早期诊断提供了一个新的技术途径。
Abstract:
To address the challenge of accurately identifying low-abundance circulating tumor cell (CTC) in whole blood samples, where interference from abundant normal blood cells complicates detection, a dynamic blood circulation platform was developed. The proposed platform integrated microfluidic vascular-like chips with peristaltic pumps, employing bright-field high-speed imaging and YOLOv11 object detection to enable label-free CTC detection in whole blood. The system simulated blood flow using a peristaltic pump, creating a flowing environment with circulatory characteristics. The chip employed multi-level branching and a 40 μm micro-screen structure, with channel dimensions optimized according to cell and vascular sizes. An image dataset comprising four cell types, including CTC (human colon cancer cell HT29 model), RBC, WBC, and PLT, was constructed. The experimental results showed that the mAP of the system for CTC detection was 98.65%, and the Precision and Recall were both greater than 99%. Continuous frame online detection was demonstrated. The system could simulate in vitro blood circulation and accurately identify CTC in whole blood samples, exhibiting high accuracy and stability. It provided a novel technical approach for early tumor diagnosis.

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备注/Memo

备注/Memo:
收稿日期:2025-10-11;修订日期:2025-11-21
基金项目:国家自然科学基金资助项目(62574188)
作者简介:李浩亮(1978— ) ,男,河南南阳人,郑州大学副教授,博士,主要从事数模混合集成电路设计研究,E-mail: iehlli@zzu.edu.cn。
通信作者:杨潇楠(1983— ) ，男，河南驻马店人，郑州大学教授，博士，博士生导师，主要从事微流控芯片与POCT、感存算一体化芯片与系统、医学人工智能类脑芯片研究，E-mail: iexnyang@zzu.edu.cn。
更新日期/Last Update: 2026-02-26