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Tracking droplets fusion in microfluidic chamber with #TrackMate, a short thread.
Yesterday I got to discuss with Liridon Aliti (on forum.image.sc) about detecting droplet fusion events in movies like this one:
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Yesterday I got to discuss with Liridon Aliti (on forum.image.sc) about detecting droplet fusion events in movies like this one:
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We tried to do it in TrackMate, it was fun and I would like to share how we did it. It serves as a demo of the new TrackMate capabilities, but was done in <10min per movie, so it should not be considered a thorough analysis (we only tried one detector one tracker).
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The droplet are border objects, so using the excellent morphological segmentation in Fiji #MorphoLibJ by @david_legland and @IgnacioArganda seemed like a good idea. Plus the image quality is incredibly good given the fps (2k here)
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New #TrackMate version out (v&7)
With major changes and improvements I describe below (probably a long thread).
It is the product of a great (and cool) collaboration with @guijacquemet lab (@JwPylvanainen), the @DumenilLab lab in @institutpasteur and the IAH facility
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With major changes and improvements I describe below (probably a long thread).
It is the product of a great (and cool) collaboration with @guijacquemet lab (@JwPylvanainen), the @DumenilLab lab in @institutpasteur and the IAH facility
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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,
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so that they can be used in a tracking pipeline and improve the tracking accuracy and results.
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