Zhang Hanqing, Söderholm Niklas, Sandblad Linda, Wiklund Krister, Andersson Magnus
Department of Physics,Umeå University,901 87 Umeå,Sweden.
Department of Molecular Biology,Umeå University,901 87 Umeå,Sweden.
Microsc Microanal. 2019 Jun;25(3):711-719. doi: 10.1017/S1431927619000308. Epub 2019 Mar 21.
Analysis of numerous filamentous structures in an image is often limited by the ability of algorithms to accurately segment complex structures or structures within a dense population. It is even more problematic if these structures continuously grow when recording a time-series of images. To overcome these issues we present DSeg; an image analysis program designed to process time-series image data, as well as single images, to segment filamentous structures. The program includes a robust binary level-set algorithm modified to use size constraints, edge intensity, and past information. We verify our algorithms using synthetic data, differential interference contrast images of filamentous prokaryotes, and transmission electron microscopy images of bacterial adhesion fimbriae. DSeg includes automatic segmentation, tools for analysis, and drift correction, and outputs statistical data such as persistence length, growth rate, and growth direction. The program is available at Sourceforge.
图像中众多丝状结构的分析常常受到算法准确分割复杂结构或密集群体中结构能力的限制。如果在记录图像时间序列时这些结构持续生长，问题就会更加严重。为克服这些问题，我们提出了DSeg；一个旨在处理时间序列图像数据以及单幅图像以分割丝状结构的图像分析程序。该程序包括一种经过改进的强大的二进制水平集算法，该算法使用尺寸约束、边缘强度和过往信息。我们使用合成数据、丝状原核生物的微分干涉对比图像以及细菌粘附菌毛的透射电子显微镜图像来验证我们的算法。DSeg包括自动分割、分析工具和漂移校正，并输出诸如持续长度、生长速率和生长方向等统计数据。该程序可在Sourceforge上获取。
