Panconi Luca, Makarova Maria, Lambert Eleanor R, May Robin C, Owen Dylan M
Institute of Immunology and Immunotherapy, School of Mathematics and Centre of Membrane Proteins and Receptors, University of Birmingham, Birmingham, UK.
Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK.
J Biophotonics. 2023 Mar;16(3):e202200199. doi: 10.1002/jbio.202200199. Epub 2022 Nov 25.
Cell segmentation refers to the body of techniques used to identify cells in images and extract biologically relevant information from them; however, manual segmentation is laborious and subjective. We present Topological Boundary Line Estimation using Recurrence Of Neighbouring Emissions (TOBLERONE), a topological image analysis tool which identifies persistent homological image features as opposed to the geometric analysis commonly employed. We demonstrate that topological data analysis can provide accurate segmentation of arbitrarily-shaped cells, offering a means for automatic and objective data extraction. One cellular feature of particular interest in biology is the plasma membrane, which has been shown to present varying degrees of lipid packing, or membrane order, depending on the function and morphology of the cell type. With the use of environmentally-sensitive dyes, images derived from confocal microscopy can be used to quantify the degree of membrane order. We demonstrate that TOBLERONE is capable of automating this task.
细胞分割是指用于识别图像中的细胞并从中提取生物学相关信息的一系列技术；然而，手动分割既费力又主观。我们提出了使用相邻发射递归的拓扑边界线估计（TOBLERONE），这是一种拓扑图像分析工具，它识别持久的同调图像特征，与通常采用的几何分析相反。我们证明，拓扑数据分析可以为任意形状的细胞提供准确的分割，为自动和客观的数据提取提供一种方法。生物学中特别感兴趣的一个细胞特征是质膜，根据细胞类型的功能和形态，质膜已被证明呈现出不同程度的脂质堆积或膜有序性。通过使用对环境敏感的染料，来自共聚焦显微镜的图像可用于量化膜有序程度。我们证明TOBLERONE能够自动完成这项任务。
