5/ A 70+ manual for the new features, included in the preprint. It includes step-by-step user tutorials and developer documentation for extending TrackMate
A 2nd post about the new #TrackMate version:
Using TrackMate to segment 3D objects using a slice-by-slice approach.
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Now that we have nice Deep-Learning based and Machine-Learning based segmentation algorithms that work especially well in 2D, we can use them to segment 3D objects with TrackMate.
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The idea is to tell TrackMate "this is not a 3D image but a 2D+T image that you will track".
For instance you could use StarDist on the individual 2D slice to segment sections of the object, then merging the multiple 2D contours in a single 3D object.
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The new version is the product of an almost Codiv19-induced full rewrite of TrackMate. Our main goal was to allow integrate SOTA segmentation algorithms and tools such as #StarDist, @ilastik_team, #Weka, @MorphoLibJ and #cellpose in TrackMate,
2/n
so that they can be used in a tracking pipeline and improve the tracking accuracy and results.
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