![]() ![]() LAY DESCRIPTION: Electron tomography of biological samples is used for a three-dimensional (3D) reconstruction of filamentous structures, such as microtubules (MTs) in mitotic and meiotic spindles. The final solution presented here is the result of an iterative process with tight feedback loops between the involved computer scientists and cell biologists. The key to our solution is a careful design of the visualisation and interaction tools for each processing step to guarantee real-time response, and an optimised workflow that efficiently guides the user through datasets. To the best of our knowledge, it is the only currently available tool which is able to process data of the type and size presented here. Here, we present a specialised, interactive, semi-automatic solution that considers all requirements for large-scale stitching of filamentous structures in serial-section image stacks. Furthermore, an interactive visualisation of the full image stack is hampered by the size of the data (up to 100 GB). However, due to the large number of MTs in spindles (up to 30k) and their resulting dense spatial arrangement, a naive inspection of each MT is too time-consuming. To derive 3D models of spindles despite dealing with imperfect data related to sample preparation and subsequent data collection, semi-automatic validation and correction is required to remove stitching mistakes. In practice, automatic stitching alone provides only an incomplete solution, because large physical distortions and a low signal-to-noise ratio often cause experimental difficulties. The serial tomograms are then stitched and non-rigidly aligned to allow tracing and connecting of MTs across tomogram boundaries. For this, each spindle is cut into a series of semi-thick physical sections, of which electron tomograms are acquired. The software tool was developed in an interdisciplinary collaboration between computer scientists and cell biologists to investigate cell division by quantitative 3D analysis of microtubules (MTs) in both mitotic and meiotic spindles. Supported by a visual quality assessment of regions that have been already inspected, this allows a trade-off between quality and manual labour. ![]() ![]() After the computation of an initial automatic matching, the user can continuously improve the result by interactively correcting landmarks or matches of filaments. This is achieved by combining automatic methods, visual validation, and interactive correction. We present a software-assisted workflow for the alignment and matching of filamentous structures across a three-dimensional (3D) stack of serial images. ![]()
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