Suppr超能文献

一种用于在荧光显微镜延时拍摄中分割和跟踪聚集细胞的稳健算法。

A robust algorithm for segmenting and tracking clustered cells in time-lapse fluorescent microscopy.

出版信息

IEEE J Biomed Health Inform. 2013 Jul;17(4):862-9. doi: 10.1109/JBHI.2013.2262233.

Abstract

We present herein a robust algorithm for cell tracking in a sequence of time-lapse 2-D fluorescent microscopy images. Tracking is performed automatically via a multiphase active contours algorithm adapted to the segmentation of clustered nuclei with obscure boundaries. An ellipse fitting method is applied to avoid problems typically associated with clustered, overlapping, or dying cells, and to obtain more accurate segmentation and tracking results. We provide quantitative validation of results obtained with this new algorithm by comparing them to the results obtained from the established CellProfiler, MTrack2 (plugin for Fiji), and LSetCellTracker software.

摘要

我们在此提出了一种强大的算法,用于对时滞 2-D 荧光显微镜图像序列中的细胞进行跟踪。通过一种多相主动轮廓算法进行自动跟踪,该算法适用于分割具有模糊边界的聚集核。应用椭圆拟合方法可以避免与聚集、重叠或死亡细胞相关的问题,并获得更准确的分割和跟踪结果。我们通过将该新算法获得的结果与 CellProfiler、MTrack2( Fiji 的插件)和 LSetCellTracker 软件获得的结果进行比较,对该算法的结果进行了定量验证。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验