A novel universal algorithm for filament network tracing and cytoskeleton analysis
| Autor: | Daniel A. D. Flormann, Divyendu Goud Thalla, Moritz Schu, Annica K. B. Gad, Marcus Koch, Franziska Lautenschläger, Emmanuel Terriac, Lucina Kainka |
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| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
0301 basic medicine
intermediate filaments Computer science ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Retinal Pigment Epithelium Tracing Biochemistry Grayscale Protein filament microtubules 03 medical and health sciences 0302 clinical medicine Software image analysis Microscopy Genetics Image Processing Computer-Assisted Humans Pseudopodia Cytoskeleton Molecular Biology Cells Cultured business.industry cytoskeleton Thresholding Range (mathematics) Actin Cytoskeleton 030104 developmental biology Microscopy Electron Scanning business Algorithm actin 030217 neurology & neurosurgery Algorithms Biotechnology |
| DOI: | 10.22028/d291-35456 |
| Popis: | The rapid development of advanced microscopy techniques over recent decades has significantly increased the quality of imaging and our understanding of subcellular structures, such as the organization of the filaments of the cytoskeleton using fluorescence and electron microscopy. However, these recent improvements in imaging techniques have not been matched by similar development of techniques for computational analysis of the images of filament networks that can now be obtained. Hence, for a wide range of applications, reliable computational analysis of such two-dimensional (2D) methods remains challenging. Here, we present a new algorithm for tracing of filament networks. This software can extract many important parameters from grayscale images of filament networks, including the Mesh Hole Size, and Filament Length and Connectivity (also known as Coordination Number. In addition, the method allows sub-networks to be distinguished in 2D images using intensity thresholding. We show that the algorithm can be used to analyze images of cytoskeleton networks obtained using different advanced microscopy methods. We have thus developed a new improved method for computational analysis of 2D images of filamentous networks that has wide applications for existing imaging techniques. The algorithm is available as open-source software. |
| Databáze: | OpenAIRE |
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