Yerly Jerome, Hu Yaoping, Jones Steven M, Martinuzzi Robert J
Electrical and Computer Engineering, Schulich School of Engineering, University of Calgary, 2500 University Drive NW, Calgary, AB, Canada T2N 1N4.
J Microbiol Methods. 2007 Sep;70(3):424-33. doi: 10.1016/j.mimet.2007.05.022. Epub 2007 Jun 16.
This paper presents a robust two-step segmentation procedure for the study of biofilm structure. Without user intervention, the procedure segments volumetric biofilm images generated by a confocal laser scanning microscopy (CLSM). This automated procedure implements an anisotropic diffusion filter as a preprocessing step and a 3D extension of the Otsu method for thresholding. Applying the anisotropic diffusion filter to even low-contrast CLSM images significantly improves the segmentation obtained with the 3D Otsu method. A comparison of the results for several CLSM data sets demonstrated that the accuracy of this procedure, unlike that of the objective threshold selection algorithm (OTS), is not affected by biofilm coverage levels and thus fills an important gap in developing a robust and objective segmenting procedure. The effectiveness of the present segmentation procedure is shown for CLSM images containing different bacterial strains. The image saturation handling capability of this procedure relaxes the constraints on user-selected gain and intensity settings of a CLSM. Therefore, this two-step procedure provides an automatic and accurate segmentation of biofilms that is independent of biofilm coverage levels and, in turn, lays a solid foundation for achieving objective analysis of biofilm structural parameters.
本文提出了一种用于生物膜结构研究的稳健两步分割程序。无需用户干预，该程序即可对共聚焦激光扫描显微镜（CLSM）生成的生物膜体积图像进行分割。此自动化程序将各向异性扩散滤波器作为预处理步骤，并采用大津法的三维扩展进行阈值处理。将各向异性扩散滤波器应用于对比度低的CLSM图像，能显著改善三维大津法获得的分割效果。对多个CLSM数据集的结果比较表明，该程序的准确性与客观阈值选择算法（OTS）不同，不受生物膜覆盖水平的影响，从而填补了开发稳健且客观的分割程序方面的重要空白。对于包含不同细菌菌株的CLSM图像，展示了当前分割程序的有效性。该程序的图像饱和度处理能力放宽了对用户选择的CLSM增益和强度设置的限制。因此，这个两步程序提供了一种独立于生物膜覆盖水平的生物膜自动准确分割方法，进而为实现生物膜结构参数的客观分析奠定了坚实基础。
