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Displaying posts with the tag: is_archive

TrackMate-Oneat: Auto Track correction using deep learning networks

Posted by , on 4 July 2022

During the tracking of motile cells, solving the problem of linking objects between two consecutive timepoints becomes even more complicated, if the cells divide or undergo cell death. In the terms of trajectories, this means the addition of trajectory branches and terminations. However, dividing and dying cells are characteristic in their shape, and leveraging this

Etch A Cell - segmenting electron microscopy data with the power of the crowd

Posted by , on 16 July 2020

Recent years have seen remarkable developments in imaging techniques and technologies, producing increasingly rich datasets that require huge amounts of costly technological infrastructure, computational power and researcher effort to process. Techniques such as light-sheet microscopy and volume electron microscopy routinely generate terabytes worth of data overnight. With a single data acquisition producing more images than