Speaker
Description
Recent new developments in microscopy image analysis are heavily biased towards blob-like structures (cells, nuclei, vesicles), while tools for the exploration of filaments or curvilinear objects (spines, biopolymers, neurites, vessels, cilia) are often underrepresented. To address this gap, we developed the BigTrace plugin for Fiji, powered by the imglib2 library and using BigVolumeViewer for the visualization. It works with arbitrary large (and small) 3D multi-channel, timelapse images and allows lazy loading from proprietary formats and on-the-fly deskewing. BigTrace semi-automatically traces filament structures and performs spline interpolation and extraction of underlying volumetric intensity data for analysis. Its application will be illustrated be three user cases. First is the tracing of microtubules in the dense arrays of cardiovascular cells obtained using expansion microscopy. The second is the analysis of cytoplasmic bridges in the volumetric timelapse lattice light-sheet recordings of 3D dividing cells. The last one is the extraction of basal bodies and cilia from in situ organoid cultures of airway epithelia for the aim of protein mapping using averaging of 3D volumes.
| Authors | Eugene A. Katrukha*, Lukas Kapitein |
|---|---|
| Keywords | curvilinear structures, filaments, 3D microscopy, big data |
