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

Explorative image data science with napari

Posted by , on 23 May 2022

When analysing microscopy image data of biological systems, a major bottleneck is to identify image-based features that describe the phenotype we observe. For example when characterising phenotypes of nuclei in 2D images, often questions come up such as “Shall we use circularity, solidity, extend, elongation, aspect radio, roundness or Feret’s diameter to describe the shape