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Bringing TrackMate into the era of machine-learning and deep-learning

Authors :
Guillaume Jacquemet
Nathan H. Roy
Laure Le Blanc
Stéphane Rigaud
Minh-Son Phan
James R.W. Conway
Daria Bonazzi
Joanna W Pylvänäinen
Guillaume Duménil
Romain F. Laine
Arthur Charles-Orszag
Jean-Yves Tinevez
Dmitry Ershov
Publication Year :
2021
Publisher :
Cold Spring Harbor Laboratory, 2021.

Abstract

TrackMate is an automated tracking software used to analyze bioimages and distributed as a Fiji plugin. Here we introduce a new version of TrackMate rewritten to improve performance and usability, and integrating several popular machine and deep learning algorithms to improve versatility. We illustrate how these new components can be used to efficiently track objects from brightfield and fluorescence microscopy images across a wide range of bio-imaging experiments.

Details

Database :
OpenAIRE
Accession number :
edsair.doi...........05dc336f8c8ddbf5d90dbd056cccec14