文献类型：期刊文献

英文题名：HFM-Tracker: a cell tracking algorithm based on hybrid feature matching

作者：Zhao, Yan[1];Chen, Ke-Le[2];Shen, Xin-Yu[3];Li, Ming-Kang[2];Wan, Yong-Jing[1];Yang, Cheng[3];Yu, Ru-Jia[2];Long, Yi-Tao[2];Yan, Feng[3];Ying, Yi-Lun[1,4]

机构：[1]East China Univ Sci & Technol, Sch Informat Sci & Engn, 130 Meilong Rd, Shanghai 200237, Peoples R China;[2]Nanjing Univ, Mol Sensing & Imaging Ctr MSIC, Sch Chem & Chem Engn, Nanjing 210023, Peoples R China;[3]Nanjing Univ, Sch Elect Sci & Engn, Nanjing 210023, Peoples R China;[4]Nanjing Univ, Chem & Biomed Innovat Ctr, Nanjing 210023, Peoples R China

年份：2024

卷号：149

期号：9

起止页码：2629

外文期刊名：ANALYST

收录：;EI(收录号：20241515873800);WOS:【SCI-EXPANDED(收录号:WOS:001195070600001)】；

基金：This work was supported by the National Key Research and Development Program of China (No. 2022YFA1205004), the National Natural Science Foundation of China (22276089), and Programs for High-Level Entrepreneurial and Innovative Talents Introduction of Jiangsu Province.

语种：英文

外文关键词：Cytology - Tracking (position)

摘要：Cell migration is known to be a fundamental biological process, playing an essential role in development, homeostasis, and diseases. This paper introduces a cell tracking algorithm named HFM-Tracker (Hybrid Feature Matching Tracker) that automatically identifies cell migration behaviours in consecutive images. It combines Contour Attention (CA) and Adaptive Confusion Matrix (ACM) modules to accurately capture cell contours in each image and track the dynamic behaviors of migrating cells in the field of view. Cells are firstly located and identified via the CA module-based cell detection network, and then associated and tracked via a cell tracking algorithm employing a hybrid feature-matching strategy. This proposed HFM-Tracker exhibits superiorities in cell detection and tracking, achieving 75% in MOTA (Multiple Object Tracking Accuracy) and 65% in IDF1 (ID F1 score). It provides quantitative analysis of the cell morphology and migration features, which could further help in understanding the complicated and diverse cell migration processes. A novel cell tracking algorithm, named HFM-Tracker (Hybrid Feature Matching Tracker), is proposed to accurately track the migratory behavior of cells through the capture of time-lapse cell images.