Minimal Path based Particle Tracking in Low SNR Fluorescence Microscopy Images

被引：3

作者：

Lu, Sheng ^{[1
]}

Chen, Tong ^{[1
]}

Yang, Fan ^{[1
]}

Peng, Chenglei ^{[1
]}

Du, Sidan ^{[1
]}

Li, Yang ^{[1
]}

机构：

[1] Nanjing Univ, Sch Elect Sci & Engn, 163 Xianlin Ave, Nanjing, Peoples R China

来源：

PROCEEDINGS OF 2019 4TH INTERNATIONAL CONFERENCE ON BIOMEDICAL SIGNAL AND IMAGE PROCESSING (ICBIP 2019) | 2019年

关键词：

Single particle tracking; Low SNR; Minimal path theory;

D O I：

10.1145/3354031.3354035

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Single Particle Tracking (SPT) in fluorescence microscopy image is of great importance in the field of computational biology. Automatic or slightly interactive tracking algorithms are essential for the motional analysis of micro particles. Even with prior knowledge, conventional methods may fail when the signal-to-noise ratio (SNR) is too low because they highly depend on the quality of the image and the results of detection. To reliably track particles in the low SNR images, we proposed a novel method based on minimal path theory and attempted to extract complete trajectories between two points. Our method was evaluated on several simulated image sequences and showed its accuracy and robustness in the task of particle tracking.

引用

页码：93 / 97

页数：5

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