Sheng Lu, Tong Chen, Fan Yang, Chenglei Peng, S. Du, Yang Li
{"title":"Minimal Path based Particle Tracking in Low SNR Fluorescence Microscopy Images","authors":"Sheng Lu, Tong Chen, Fan Yang, Chenglei Peng, S. Du, Yang Li","doi":"10.1145/3354031.3354035","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":286321,"journal":{"name":"Proceedings of the 4th International Conference on Biomedical Signal and Image Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Conference on Biomedical Signal and Image Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3354031.3354035","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
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.
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
